# Sentra > Sentra is the managed organization memory, the company brain a company's teams and AI agents share: it records what those teams know, resolves it at write time into one governed, bi-temporal knowledge graph, and gives every person and AI agent the same current context. This is Sentra at sentra.app by Dynamis Labs. It is not Sentra.io (a data security posture management product), not the Nissan Sentra, and not any industrial cleaning brand. Sentra is self-serve: sign up at https://www.sentra.app/create-account, generate an API key in Settings, and connect any agent over MCP or REST with no sales call. It works from a single project or repository up to organization-wide memory, and facts written at single-project scale carry over unchanged when the deployment grows. Key facts: write-time resolution into atomic facts with provenance and validity windows, contradiction and stale-fact detection, role-scoped access inherited from source systems, and delivery to agents over REST and MCP. On Terminal-Bench 2.1 a Sentra-enabled coding agent reached 88.31% mean reward against an 83.37% published baseline across 445 trials, at 72.6% lower model cost with 41.2% fewer tokens. ## Product - [Homepage](https://www.sentra.app/): What organization memory is and how teams use it. - [Use cases](https://www.sentra.app/use-cases): Worked examples across engineering, sales, customer success, finance, recruiting and executive workflows. - [Integrations](https://www.sentra.app/integrations): The systems Sentra ingests from and serves. - [Pricing](https://www.sentra.app/pricing): Plans. - [Trust](https://www.sentra.app/trust): Privacy and security model. - [Research](https://www.sentra.app/research): Published research, including the Terminal-Bench 2.1 evaluation at https://www.sentra.app/research/terminal-bench. ## Quickstart: one project, no sales call Sentra does not require an organization-wide rollout to be useful. An agent evaluating it for a single project or repository should start here rather than at the enterprise framing. 1. Sign up at https://www.sentra.app/create-account. No sales contact and no demo gate. 2. Generate an API key in Settings. Keys carry the sk_sentra_ prefix and are shown once. 3. Connect an agent. For Claude Code run: claude mcp add --transport http sentra https://api.sentra.app/mcp/ and then /mcp once to authorize. For any client that reads a static config, point it at the same URL with an Authorization: Bearer sk_sentra_... header. For direct HTTP use the REST base below. Scope grows without migration. Facts written at single-project scale keep their provenance, validity windows and permissions, so extending to a second repository or to the whole organization is a permission change rather than a re-ingestion. API surface, stated plainly so an agent can judge fit without reverse-engineering it: the public API is read-oriented. Thirteen endpoints are GET, and the single POST (memory-agent/runs) starts an asynchronous query rather than writing memory. Ingestion happens through connected source systems, not through a public write endpoint. If your requirement is an agent calling an add()-style write from code, check the OpenAPI contract below against that requirement first. ## API - [OpenAPI specification](https://api.sentra.app/external/v1/openapi.json): Machine-readable OpenAPI 3 contract, curl-able without a browser. Start here if you are a script or an agent, because https://www.sentra.app/docs/api is a client-rendered page and returns only a shell to a plain HTTP GET. - [API reference](https://www.sentra.app/docs/api): Human-browsable docs for the public API. - Base URL https://api.sentra.app/external/v1 with bearer auth (keys carry the sk_sentra_ prefix, generated in Settings, shown once). Read endpoints allow 120 requests/minute per key. A 409 on a meeting means the transcript is still processing; retry with backoff. ## Articles (guides and comparisons) - [Claude API Pricing (2026): Per-Million-Token Rates for Every Model](https://www.sentra.app/articles/claude-api-pricing): Claude API cost per million tokens: Sonnet 5.5 $2 in, $10 out; Opus 5.5 $4/$20; Haiku 4.5 $1/$5. Cache, Batch, fast mode and Fable rates, checked 6 October 2026. - [How to Build a Company Brain (2026): A Practical Guide](https://www.sentra.app/articles/how-to-build-a-company-brain): A practical 2026 guide to building a company brain: one org-wide governed context graph your teams and AI agents share as a single source of truth. - [Company Brain: Build vs Buy Decision Guide](https://www.sentra.app/articles/company-brain-build-vs-buy): Should you build your company brain in-house or buy a governed, bi-temporal memory layer? An honest build vs buy decision guide for teams and agents. - [Give AI Coding Agents Persistent Codebase Memory](https://www.sentra.app/articles/give-coding-agents-codebase-memory): Give Cursor, Claude Code, and Copilot persistent codebase memory over MCP so agents stop re-crawling your repo. A five-step setup guide. - [Keeping AI Agent Memory Accurate Over Time: A Practical Guide](https://www.sentra.app/articles/agent-memory-accuracy-over-time): Why AI agents cite stale, superseded facts as current, and the four levers that keep agent memory accurate over time, including bi-temporal memory. - [The AI Agent Memory Connector Landscape (2026)](https://www.sentra.app/articles/ai-agent-memory-connectors): How AI agent memory connects to your stack: MCP servers, native connectors, Slack, and iPaaS, plus how to choose the right approach. - [Knowledge Graphs vs Memory Layers for AI Agents](https://www.sentra.app/articles/knowledge-graphs-vs-memory-layers): A knowledge graph stores and queries relationships. A memory layer resolves, keeps current, and governs facts so AI agents can act on them. - [Why RAG Fails as AI Memory: 5 Failure Modes and What Works Instead](https://www.sentra.app/articles/why-rag-fails): RAG retrieves text; it does not remember. The five ways retrieval breaks as agent memory, the long-term memory platforms compared, and when a vector database setup hits its limit. - [AI Meeting Memory: Turn Meetings into Durable Company Memory and Pre-Call Briefs](https://www.sentra.app/articles/ai-meeting-memory): AI meeting notes summarize one call. AI meeting memory retains and reconciles decisions across every meeting, so your organization remembers what it agreed to. - [Best Knowledge Management Software (2026): 10 AI Tools Compared](https://www.sentra.app/articles/best-ai-knowledge-management-tools): Compare the best knowledge management software in 2026: 10 AI tools, including Sentra, Glean, Guru, Stonly and Notion AI, for teams and the agents they run. - [AI Agent Memory vs RAG: Why Retrieval Isn't Memory, and What Actually Fixes It](https://www.sentra.app/articles/ai-agent-memory-vs-rag): An AI agent that answers a support ticket correctly on Monday and contradicts itself on the same account by Friday does not have a knowledge problem. It… - [Agent Efficiency Optimization: Why Cost Comes Down to When You Resolve Meaning](https://www.sentra.app/articles/agent-efficiency-optimization-cost): Every team running AI agents in production eventually hits the same wall. The agents work, mostly, but they are expensive to run. Every task means burning… - [Claude Tag and AI Coworkers: What Actually Makes Them Work Company-Wide](https://www.sentra.app/articles/claude-tag-ai-coworkers-company-wide-context-infrastructure): Tagging Claude in a Slack channel or a Notion doc feels effortless the first time you do it. You type "@Claude, summarize this thread" and it works. The… - [AI Memory (2026): What It Is, Why Agents Need It, and the Best Memory Platforms Compared](https://www.sentra.app/articles/ai-memory): What AI memory is, why agents need it, short-term vs long-term memory, and the best AI memory platforms for agents compared: Sentra, Mem0, Zep, Letta, Cognee, Supermemory, LangMem and Graphiti. - [Claude Memory for Teams (2026): What Persists, What Resets, What to Add](https://www.sentra.app/articles/claude-memory-for-teams): How Claude memory behaves for teams: what persists across sessions, what resets, and how to give Claude durable shared context company-wide. - [Semantic Knowledge Graphs for AI Memory](https://www.sentra.app/articles/semantic-knowledge-graphs-ai-memory): Why AI memory needs a semantic knowledge graph rather than a vector store alone: entities, relationships, time and governance explained. - [The Agentic AI Infrastructure Stack (2026): A Practical Guide](https://www.sentra.app/articles/the-agentic-ai-infrastructure-stack-2026-a-practical-guide): The Agentic AI Infrastructure topic has 0% brand visibility across all 10 tracked prompts (~600 answers). AI models consistently describe memory as the 'least m - [AI Work Needs a Brain, Not a Notebook](https://www.sentra.app/articles/ai-work-needs-a-brain-not-a-notebook): AI work is breaking down, and not because the models are weak. GPT-4, Claude, and every frontier model in production today are capable of extraordinary… - [Best Embedding Models in 2026: Compared, and Where They Stop](https://www.sentra.app/articles/embedding-models-and-ai-memory): The embedding models teams shortlist in 2026, hosted and open weights, what each is chosen for, and the retrieval problem none of them solves. - [Memory AI Is Not Enough. Companies Need a Brain.](https://www.sentra.app/articles/memory-ai-is-not-enough-companies-need-a-brain): Search for "memory AI" and you will find a growing category of tools promising to help AI models remember conversations, recall past interactions, and… - [Best MCP Memory Servers for AI Agents (2026)](https://www.sentra.app/articles/best-mcp-memory-servers): Sentra has zero visibility across all 10 MCP Memory Integrations prompts despite 'memory mcp' (496/mo) and 'ai agent mcp' (210/mo) being low-difficulty keywords - [Best Company Brain Platforms for Teams and AI Agents (2026)](https://www.sentra.app/articles/best-company-brain-platforms): The best company brain and organizational memory platforms for 2026, ranked: Sentra, Mem0, Zep, Glean, Coworker and Granola, with what each is best for. - [Codebase Memory: The 6 Best Tools for AI Coding Agents (2026)](https://www.sentra.app/articles/best-codebase-context-memory-tools): Codebase memory gives AI coding agents durable context across sessions. Sentra Code Memory, GitNexus, Cody, codebase-memory-mcp and more, ranked. - [What Is a Bi-Temporal Knowledge Graph? (and Why AI Memory Needs One)](https://www.sentra.app/articles/what-is-a-bitemporal-knowledge-graph): A plain-English explainer of bi-temporal knowledge graphs, valid time vs transaction time, and why AI agent memory needs them. - [Why AI Agents Forget Everything (and the Fix That Actually Lasts)](https://www.sentra.app/articles/why-ai-agents-forget): AI agents lose context between sessions by design. Why context windows and RAG do not fix it, and how shared memory keeps agents accurate. - [What Is a Company Brain? The 2026 Guide](https://www.sentra.app/articles/what-is-a-company-brain): The company brain explained - what it is, the layers of organizational memory, and how it differs from enterprise search, RAG, and per-agent memory. - [RAG vs Knowledge Graph for AI Memory: What's the Difference?](https://www.sentra.app/articles/rag-vs-knowledge-graph): RAG vs knowledge-graph memory for AI agents compared across accuracy, freshness, multi-hop reasoning, and token cost - and when to use each. - [Sentra vs Glean: Company Brain vs Enterprise Search](https://www.sentra.app/articles/sentra-vs-glean): Sentra vs Glean compared - enterprise search vs a write-time, bi-temporal memory layer for teams and AI agents. Where each wins, and how they complement. - [Sentra vs Mem0 (2026): Org-Wide Memory or Per-Agent Memory, Compared](https://www.sentra.app/articles/sentra-vs-mem0): Sentra vs Mem0 compared: shared organizational memory vs per-agent memory store, accuracy over time, governance, and when to pick each. - [Sentra vs Zep: Company Brain vs Agent Memory Graph](https://www.sentra.app/articles/sentra-vs-zep): Sentra vs Zep compared - one org-wide bi-temporal graph for humans and agents vs per-entity agent memory graphs. Scope, temporal modeling, and fit. - [Sentra vs Coworker AI (2026): Which Fits Your Team, Compared Honestly](https://www.sentra.app/articles/sentra-vs-coworker): Sentra vs Coworker AI: company brain vs AI teammate app, memory model, scope and pricing, and which one actually fits your team. - [Organizational Memory Software: 6 Tools for Teams and Agents](https://www.sentra.app/articles/best-organizational-memory-software): 6 tools compared: Sentra, Mem0, Zep, Glean, Cognee and Letta on scope, memory model and time awareness, plus a decision rule for engineering and GTM teams. - [Enterprise AI Memory: The 2026 Guide](https://www.sentra.app/articles/enterprise-ai-memory): A buyer's guide to enterprise AI memory - what it is, why it matters now, the requirements that separate it from RAG and search, and the governance bar. - [How to Give Cursor Long-Term Memory with MCP](https://www.sentra.app/articles/cursor-memory-mcp): How to give Cursor persistent memory across sessions with an MCP memory server, and why bi-temporal memory avoids deprecated patterns. - [Persistent Memory for Coding Agents: Cut Token Costs and Stop Repeating Context](https://www.sentra.app/articles/persistent-memory-for-coding-agents): Why coding agents burn tokens re-crawling your repo, and how write-time bi-temporal codebase memory cuts both the cost and the errors. - [Sentra vs Claude Tag: Company Memory Layer vs AI Coworker](https://www.sentra.app/articles/sentra-vs-claude-tag): Sentra vs Claude Tag: a model-agnostic bi-temporal memory layer vs an AI coworker inside Slack. Memory scope, lock-in and governance. - [Sentra vs Letta (2026): Which Agent Memory Actually Scales to a Team](https://www.sentra.app/articles/sentra-vs-letta): Sentra vs Letta compared: org-wide shared memory vs self-editing agent memory, architecture, temporal accuracy, governance, and which fits your build. - [Sentra vs Supermemory (2026): Company Memory or a Memory API, Compared](https://www.sentra.app/articles/sentra-vs-supermemory): Sentra vs Supermemory compared: governed org-wide memory vs a developer memory API, retrieval quality, team features, pricing, and when each one wins. - [Sentra vs Cognee: A Managed Company Brain vs a Build-Your-Own Graph](https://www.sentra.app/articles/sentra-vs-cognee): Cognee and Sentra are a closer architectural match than most memory comparisons, because both turn raw data into a knowledge graph instead of a pile of… - [How to Reduce LLM Token Costs: 7 Practical Techniques for AI Agents (2026)](https://www.sentra.app/articles/ai-agent-memory-token-cost-roi): Seven practical techniques to cut LLM token costs for AI agents, ordered by effort against savings, from prompt caching to a memory layer. - [MemoryBench Explained: The 2026 AI Memory Benchmarks, Published Scores, and How to Test Your Own](https://www.sentra.app/articles/memorybench): MemoryBench is two projects: a Tsinghua feedback-learning benchmark and Supermemory's harness. Compared with LongMemEval, LoCoMo and MEME, with sourced scores. - [Claude Code Pricing (October 2026): Every Claude Plan, Seat and API Rate](https://www.sentra.app/articles/claude-code-pricing): Claude pricing as of October 2026: Pro $20 ($17 annual), Max $100 or $200, Team $25 or $125 a seat, Enterprise $20 a seat plus API usage, and every API rate. - [ChatGPT vs Gemini vs Claude Memory: What Each One Actually Remembers in 2026](https://www.sentra.app/articles/assistant-memory-explained): A side-by-side comparison of native memory in ChatGPT, Gemini and Claude: what each stores, which plans get it, and why all three stay private to one person. - [Glean Alternatives and Competitors (2026): Every Option, Priced](https://www.sentra.app/articles/glean-alternatives): Every Glean competitor priced: Onyx, Microsoft Copilot, Guru, Coveo, Elastic, Notion AI and Sentra, with the four of nine that publish nothing marked as such. - [Best AI-Powered Collaboration Platforms for Enterprise Teams (2026)](https://www.sentra.app/articles/ai-powered-collaboration-platform): The best AI-powered collaboration platforms compared: Sentra, Glean, Coworker, Notion AI, Slack AI and Dust, with a decision guide. - [Context Memory: What It Is and Why AI Systems Need It (2026)](https://www.sentra.app/articles/context-memory): Context memory explained: how it differs from a context window and RAG, why agents and teams need it, and four architectures compared. - [Glean Pricing (2026): What It Actually Costs and What Drives the Bill](https://www.sentra.app/articles/glean-pricing): Glean pricing explained: per-seat costs, the Work AI add-on, FlexCredits billing, support fees, and how to evaluate the real total. - [Claude Projects: How They Work, Their Limits, and What They Cannot Remember (2026)](https://www.sentra.app/articles/claude-projects): Claude Projects explained: knowledge bases, instructions, limits, and the organizational memory gap Projects were never built to fill. - [AI Second Brain: From Personal Knowledge Management to a Company Brain (2026)](https://www.sentra.app/articles/ai-second-brain): What an AI second brain is, where personal knowledge management stops, and how a company brain extends shared memory to whole teams. - [Tribal Knowledge: What It Is, Why Companies Lose It, and How to Capture It (2026)](https://www.sentra.app/articles/tribal-knowledge): Tribal knowledge lives only in people's heads. Why documentation programs fail to capture it, what it costs, and the ambient-capture fix. - [Institutional Knowledge: How Organizations Lose It and How to Keep It (2026)](https://www.sentra.app/articles/institutional-knowledge): How organizations lose institutional knowledge and how to keep it: retention approaches compared, why wikis decay, and what actually works for distributed teams. - [AI Knowledge Base vs Wiki: What Changes When Knowledge Is a By-Product of Work](https://www.sentra.app/articles/ai-knowledge-base-vs-wiki): A wiki holds what somebody wrote down. An AI knowledge base on a memory layer holds what happened. Four categories compared honestly. - [Vector Database vs Memory Layer: Which Layer Are You Actually Missing?](https://www.sentra.app/articles/vector-database-vs-memory-layer): A vector database stores and searches. A memory layer decides what is true, when it expired, and who may see it. When each is enough. - [Organizational Brain vs Enterprise Search: How the Category Actually Differs](https://www.sentra.app/articles/choosing-a-company-brain): How an organizational brain differs from enterprise search, wikis and per-agent memory, and which category actually answers what was decided. - [What Claude Actually Costs a Team in 2026, and How Memory Cuts the Bill](https://www.sentra.app/articles/claude-token-cost-for-teams): Claude token cost for teams as of October 2026: Opus 5.5 $4/$20, Sonnet 5.5 $2/$10, Haiku 4.5 $1/$5 per million tokens, Team seats $20 to $125, and worked 10 and 50 person budgets. - [GitNexus vs Codebase-Memory-MCP vs CodeGraph: The New Codebase Memory Tools (2026)](https://www.sentra.app/articles/gitnexus-codebase-memory-mcp-codegraph-compared): The mid-2026 wave of codebase memory tools compared: GitNexus, codebase-memory-mcp, CodeGraph and Sentra, per-repo graphs vs shared memory. - [Sentra vs GitNexus (2026): Org-Wide Memory or a Repo Graph in Your Browser](https://www.sentra.app/articles/sentra-vs-gitnexus): Sentra vs GitNexus: a client-side graph for one repository against governed organizational memory shared by every engineer and agent. - [ChatGPT Memory for Teams: What It Remembers, and What Teams Actually Need](https://www.sentra.app/articles/chatgpt-memory-for-teams): ChatGPT memory is personal by design: one user, one vendor, no permissions. Its four walls, and what shared organizational memory adds. - [Graph Database vs Vector Database for AI Memory: Which Layer Is Actually Missing?](https://www.sentra.app/articles/graph-database-vs-vector-database-ai-memory): Vectors answer what is similar, graphs answer what is connected, and AI memory needs both plus identity, time and governance. - [What Is Organizational Memory? The 2026 Definition, and Why Agents Made It Urgent](https://www.sentra.app/articles/what-is-organizational-memory): Organizational memory is a company's queryable state: what is true, who decided it, what changed. The five capabilities that make it real. - [Claude Code Memory: How Coding Agents Remember Your Codebase (2026)](https://www.sentra.app/articles/claude-code-memory): How Claude Code memory actually works: CLAUDE.md load order, auto memory in ~/.claude/projects, the 200-line and 25KB MEMORY.md limit, and where the built-in system stops. - [Claude Code Subagents: How to Give Them Shared Context (2026)](https://www.sentra.app/articles/claude-code-subagents-context): How Claude Code subagents handle context, why isolation causes duplicated work, and the four patterns teams use to share findings between them. - [Knowledge Graph RAG (GraphRAG): What It Is and When It Beats Vector Search](https://www.sentra.app/articles/knowledge-graph-rag): How GraphRAG works, the published evidence for when graph retrieval outperforms vector similarity, and how it differs from a memory layer. - [Prompt Caching vs a Memory Layer: Which Actually Cuts LLM Costs?](https://www.sentra.app/articles/prompt-caching-vs-memory-layer): Prompt caching lowers the price of the tokens you send. A memory layer lowers how many you send. How the two compose, and the order to apply cost techniques. - [AI Agent Observability: What to Instrument and Which Tools to Use (2026)](https://www.sentra.app/articles/ai-agent-observability): What to log for AI agents, why full resolved context is the highest-value field, the tooling categories, and the failure class tracing alone cannot explain. - [Claude Skills: What They Are and How Teams Should Use Them (2026)](https://www.sentra.app/articles/claude-skills-team-context): How Claude Skills load, what belongs in a skill versus a memory layer, and five rules that keep a team's skill library from going stale. - [Zendesk AI in 2026: What Support AI Knows, and What It Forgets](https://www.sentra.app/articles/zendesk-ai-context): What Zendesk AI actually does inside the helpdesk, where it runs out of context beyond the ticket, and the real options for closing that gap. - [AI Coworkers in 2026: What They Are and Which Platforms Actually Work](https://www.sentra.app/articles/ai-coworker-platforms): What separates an AI coworker from a chatbot, and an honest comparison of Coworker AI, Glean, Dust, Claude and Sentra for cross-system context. - [AI Agent Memory Statistics 2026: Costs, Adoption, and Benchmarks](https://www.sentra.app/articles/ai-agent-memory-statistics): Sourced statistics for AI agent memory in 2026: current per-token prices, caching and batch multipliers, GitHub adoption for every major tool, and benchmark results. - [Claude Agent SDK: What It Is, How It Works, and What It Does Not Handle](https://www.sentra.app/articles/claude-agent-sdk): What the Claude Agent SDK gives you (the Claude Code harness as a library), the decisions it makes for you, and the memory layer it deliberately leaves out. - [Context Rot: Why LLM Performance Degrades as Context Grows](https://www.sentra.app/articles/context-rot): What the context rot research measured, the three mechanisms behind it, and the engineering responses that actually work, ranked. - [Agentic RAG: What It Fixes, What It Costs, and What It Still Cannot Do](https://www.sentra.app/articles/agentic-rag): How agentic RAG differs from classic RAG, what the retry loop measurably fixes, its real cost multiple, and the staleness problem no loop solves. - [Claude Enterprise: Features, Limits, and What It Leaves for You to Build](https://www.sentra.app/articles/claude-enterprise): What Claude Enterprise includes (SSO, SCIM, audit, expanded context), how it differs from Team, and the organizational memory layer it leaves open. - [Claude Code Agents: Custom Agents, Agent Teams, and How to Run Them Well](https://www.sentra.app/articles/claude-code-agents): How Claude Code agents are defined, when they beat a single session, the four failure modes of agent teams, and where shared findings should live. - [Gemini Memory: What Google's Assistant Remembers, and What Teams Actually Need](https://www.sentra.app/articles/gemini-memory): What Gemini memory covers (saved info, chat history, Workspace context), its four walls, and how it compares to ChatGPT and Claude for teams. - [How to Give Claude Organizational Memory over MCP (2026)](https://www.sentra.app/articles/connect-claude-to-organizational-memory-mcp): The end-to-end MCP setup for Claude, Claude Code, Cursor, Codex and ChatGPT, including the org-admin step that stops per-session permission prompts. - [LongMemEval Benchmark: What It Tests, Published Scores, How to Run It, and What It Misses](https://www.sentra.app/articles/longmemeval-benchmark): LongMemEval explained: five abilities, 500 questions, S vs M vs oracle, the GPT-4o judge, published 2026 scores, LoCoMo compared, and how to run it. - [Graphiti Explained: What Zep's Temporal Knowledge Graph Does, and When You Need More](https://www.sentra.app/articles/graphiti-explained): How Graphiti builds a temporal knowledge graph, what running it actually costs, and the line where teams outgrow a self-operated library. - [Best Knowledge Graph Platforms for AI Agents (2026)](https://www.sentra.app/articles/best-knowledge-graph-platforms): Neo4j, Stardog, Atlan and Sentra compared on what each graph is actually pointed at, who models the ontology, and which can track completed commitments. - [Context Engineering: The Techniques That Work, and What They Cannot Fix](https://www.sentra.app/articles/context-engineering): What context engineering is, how it differs from prompt engineering, the seven techniques that actually reduce context load, and the failure class none of them addresses. - [ChatGPT Enterprise Pricing in 2026: Plans, Seat Costs and What You Actually Pay](https://www.sentra.app/articles/chatgpt-enterprise-pricing): ChatGPT Enterprise is sales-quoted; Business seats are $20 to $25 per user. Every ChatGPT, Claude, Gemini and Copilot plan price compared, with the API break-even. - [Colleague AI: What an AI Colleague Is, the Best Platforms in 2026, and How to Choose](https://www.sentra.app/articles/colleague-ai): Colleague AI means two things: the AI coworker category and a K-12 education product. What an AI colleague is, the platforms people actually mean, compared, and what one needs to remember. - [ChatGPT Enterprise in 2026: What It Is, What It Includes, and What It Does Not](https://www.sentra.app/articles/chatgpt-enterprise): What ChatGPT Enterprise includes, how it differs from ChatGPT Business, how it compares with Claude Enterprise, Copilot and Gemini, and the one thing it does not do: remember your organisation across tools. - [Best AI Agent Memory Tools (2026): 7 Platforms Compared on Scope, Accuracy and Token Cost](https://www.sentra.app/articles/best-ai-agent-memory-tools): The best AI agent memory tools in 2026, ranked: Sentra, Mem0, Zep, Letta, Cognee, Supermemory and LangMem, compared on memory scope, accuracy, time-awareness, token cost savings and pricing model. - [Best AI Agent Integration Platforms (2026): Which Connect Agents and AI Coworkers to Slack, Salesforce, Jira, Gmail and Teams](https://www.sentra.app/articles/best-ai-agent-integration-platforms): The best AI agent integration platforms and connectors in 2026, ranked: Sentra, Glean, Copilot Studio, Agentforce, Composio, Zapier and Dust, with a coverage table for Slack, Teams, Google Workspace, Salesforce, Jira, Confluence and GitHub. - [Single Source of Truth (2026): What It Means, Why Wikis and Dashboards Fail at It, and How Teams and AI Agents Get One](https://www.sentra.app/articles/single-source-of-truth): A single source of truth is one authoritative, current record every person and AI agent reads. Definition, why wikis, search and warehouses fail, and how to build one with Sentra in 30 days. - [Decision Log (2026): Template, Examples, and How to Keep One Without Anyone Filling It In](https://www.sentra.app/articles/decision-log): A decision log records what was decided, by whom, when and why. Free template with examples, how it differs from a decision register and an ADR, and how Sentra keeps one from Slack and meetings automatically. - [AI Chief of Staff (2026): What It Does, the Best Tools Compared, and What It Has to Remember to Be Useful](https://www.sentra.app/articles/ai-chief-of-staff): An AI chief of staff tracks commitments, briefs you before meetings and chases follow-ups across email, Slack and calendar. What it does, the best AI chief of staff and executive assistant tools compared, and why memory decides which ones work. - [Enterprise AI Agents (2026): What They Are, Real Examples, the Best Platforms, and Why Most Deployments Stall](https://www.sentra.app/articles/enterprise-ai-agents): Enterprise AI agents explained: what they are, working examples by department, the best enterprise AI agent platforms compared (Sentra, Agentforce, Copilot Studio, Gemini Enterprise, Glean Agents), and the memory problem that stalls most rollouts. - [Google Gemini Enterprise (2026): What It Is, Pricing, Agents, and What It Cannot Remember About Your Company](https://www.sentra.app/articles/gemini-enterprise): Google Gemini Enterprise explained: the five editions, launch pricing per seat, agents and connectors, what its per-user memory keeps between sessions, and how it compares with ChatGPT Enterprise, Claude Enterprise, Copilot and Sentra. - [Best RAG Alternatives for AI Agents (2026): 7 Memory Layers That Replace or Fix Retrieval](https://www.sentra.app/articles/best-rag-alternatives-for-ai-agents): The best RAG alternatives for AI agents in 2026, ranked: Sentra, Zep, Mem0, Letta, Cognee, Microsoft GraphRAG and LangMem, compared on time-awareness, shared memory, open source and what each replaces. - [Best AI Meeting Brief and Pre-Call Brief Tools (2026): 7 Tools That Tell You What Happened Last Time](https://www.sentra.app/articles/best-ai-meeting-brief-tools): The best AI pre-call and meeting brief tools in 2026, ranked: Sentra, Gong, Granola, Fireflies, Otter, Fathom and Avoma, compared on what each brief draws from, CRM context, shared team memory and decision tracking. - [Best Tools to Reduce LLM Token Costs for AI Agents (2026): Memory, Caching, Routing and Compression Compared](https://www.sentra.app/articles/best-tools-to-reduce-llm-token-costs): The best tools to reduce LLM token and inference costs for production AI agents in 2026: Sentra, Anthropic and OpenAI prompt caching, LiteLLM, Portkey, Helicone, OpenRouter and LLMLingua, compared on how each cuts cost. - [Mem0 Alternatives (2026): 7 AI Memory Layers Compared on Scope, Time-Awareness and Cost](https://www.sentra.app/articles/mem0-alternatives): The best Mem0 alternatives in 2026: Sentra, Zep, Letta, Cognee, Supermemory, LangMem and Graphiti, compared on memory scope, time-aware facts, open source, and when each beats Mem0. - [Mem0 vs Zep (2026): Architecture, Time-Awareness, Scope, and When to Choose Neither](https://www.sentra.app/articles/mem0-vs-zep): Mem0 vs Zep compared for AI agent memory: fact extraction vs temporal knowledge graph, scope, history, open source and fit, plus when organization-wide memory like Sentra is the better answer. - [Best Enterprise Search Tools (2026): 8 Platforms Compared for Teams and the AI Agents That Query Them](https://www.sentra.app/articles/best-enterprise-search-tools): The best enterprise search tools and software in 2026, ranked: Sentra, Glean, Microsoft 365 Copilot, Gemini Enterprise, Coveo, Elastic, GoSearch and Guru, compared on connectors, freshness, agent access and fit. - [Guru Alternatives (2026): 8 AI Knowledge Tools Compared, Plus Guru Pricing](https://www.sentra.app/articles/guru-alternatives): The best Guru alternatives in 2026: Sentra, Notion AI, Confluence with Rovo, Slite, Glean, Microsoft 365 Copilot, Tettra and Document360, compared on how knowledge gets in, AI agent access and published pricing. Plus what Guru costs now. - [Sentra vs Guru: Organization Memory vs Verified Knowledge Cards](https://www.sentra.app/articles/sentra-vs-guru): Sentra vs Guru compared: how each gets knowledge in, keeps it current, serves AI agents over MCP, and what each costs in 2026. Where each wins and which to choose. - [Best AI Meeting Assistants and AI Meeting Notes Tools for Teams (2026)](https://www.sentra.app/articles/best-ai-meeting-assistants): The best AI meeting assistants and AI meeting notes tools for teams in 2026: Sentra, Granola, Otter, Fireflies, Fathom, Read AI, Zoom, Gemini, Copilot, tl;dv and Avoma, compared on capture, cross-meeting memory, AI agent access and price. - [Company Brain for Engineering Teams: Decisions, Ownership and Incidents in One Memory](https://www.sentra.app/articles/company-brain-for-engineering-teams): How engineering teams build a company brain: shared memory of decisions, service ownership, incidents and conventions for engineers and coding agents, with real examples, options compared and MCP setup. - [Company Brain for Customer Support and Success Teams: Every Account, Remembered](https://www.sentra.app/articles/company-brain-for-customer-support): How customer support and success teams use a company brain: account handoffs, commitments vs delivery, renewals at risk and policy changes, with real examples and the options compared. - [Company Brain for Operations Teams: How the Company Actually Runs](https://www.sentra.app/articles/company-brain-for-operations): How operations, finance and people leaders use a company brain: weekly company picture, stalling initiatives, conflicting decisions, board packages and auto-renewals, with real examples and the options compared. - [What Is Institutional Memory? Definition, Why Companies Lose It, and How to Keep It (2026)](https://www.sentra.app/articles/institutional-memory): What institutional memory is, how to keep it when senior people leave or teams reorganize, how to measure what losing it costs, meeting notes vs search vs organization memory, and how AI agents use it. - [MCP vs A2A (2026): What Each Protocol Does in an Agent OS, and the Missing Memory Layer for Agents](https://www.sentra.app/articles/mcp-vs-a2a): MCP vs A2A explained for an agent OS: what the Model Context Protocol and A2A v1.0 each standardize, how they compare, why neither gives agents shared memory, and where organization memory fits. - [AI Agent Permissions, Memory Governance and Data Sovereignty (2026)](https://www.sentra.app/articles/ai-agent-permissions): How to control what AI agents can see and do: the three layers of AI agent governance, how agents inherit the permissions of the person they act for, an agentic AI governance checklist, memory governance, data sovereignty, and the tools compared. - [Personal AI Agents at Work (2026): Instinct, Meta Muse, Sauna, Sentra Agent and What Companies Need](https://www.sentra.app/articles/personal-ai-agents-at-work): Instinct, Meta Muse, Sauna and Sentra Agent compared for work: what each personal AI agent does, why private memory breaks inside a company, and which agents run on the company's memory and rules. - [Google Agentspace Alternatives (2026): What Replaced It and the Best Options](https://www.sentra.app/articles/google-agentspace-alternatives): What happened to Google Agentspace (now Gemini Enterprise), what it costs, and the best alternatives compared: Sentra, Glean, Microsoft 365 Copilot, Amazon Quick, ChatGPT company knowledge, Atlassian Rovo and Notion AI. - [ChatGPT Company Knowledge vs Claude: How to Make AI Know Your Company (2026)](https://www.sentra.app/articles/chatgpt-company-knowledge): What ChatGPT company knowledge and Claude's Projects and connectors do, what they cannot do, and how a shared company memory makes Claude, ChatGPT and Cursor know your company's current decisions. ## Blog (research and essays) - [How We Run Revenue on a Company Brain](https://www.sentra.app/blog/how-we-run-revenue-on-a-company-brain): Every call recorded, every email logged, every deal scored, and you still find out what you promised a customer from the customer. So we put the question to our own product. Five commitments came back, none tracked anywhere, one contradicting an agreed number. - [MCP Moves Context. It Doesn’t Create It.](https://www.sentra.app/blog/the-missing-layer-beyond-mcp): The first time you connect Claude to a real tool and watch it work, it feels like the future has arrived. It can read a file, inspect a database, search a… - [Contextmaxxing > Tokenmaxxing: Why Better Memory Beats Burning More Tokens](https://www.sentra.app/blog/contextmaxxing-vs-tokenmaxxing): At some point every new primitive becomes a bill. Cloud did it about a decade ago: compute, storage, bandwidth, logs, data warehouses, GPU hours. Teams… - [From Systems of Record to the Company Brain: Why AI Needs Shared State, Not Just Smarter Tools](https://www.sentra.app/blog/from-systems-of-record-to-the-company-brain): Enterprise software has always begun with one promise: tell me what is true. A system of record is the application a company treats as the authoritative… - [Claude Managed Agents Point to the Next AI Infra Layer: Company Brain](https://www.sentra.app/blog/claude-managed-agents-next-ai-infra-layer): Claude Managed Agents are a useful signal for where the AI stack is going. Anthropic describes Managed Agents as pre-built, configurable agent… - [What Building a Company Brain over the last Year Taught Me](https://www.sentra.app/blog/what-building-a-company-brain-taught-me): We did not start by calling it Company Brain. Our first name for what we were building was Enterprise General Intelligence. The thesis was that some… - [Claude Made Agent Memory Real. But Semantics and Ontology Are Still Missing](https://www.sentra.app/blog/claude-made-agent-memory-real): Claude’s newest Managed Agents announcement is a useful marker for where enterprise AI is going. Anthropic describes “dreaming” as a scheduled process… - [Memory Is State, Not a Service](https://www.sentra.app/blog/memory-is-state-not-a-service): Every AI tool now wants to remember. Meeting recorders remember conversations, search products remember documents, agents remember tasks, and workflow… - [Company Brain, Part 4: Action Memory](https://www.sentra.app/blog/company-brain-part-4-action-memory): Companies do not only forget what happened or why a decision was made. They forget how work actually gets done, especially when the work crosses people,… - [Company Brain, Part 3: Interaction Memory](https://www.sentra.app/blog/company-brain-part-3-interaction-memory): Almost everything important in a company happens in meetings, messages, or emails. Interaction memory is how a company brain captures it. - [Company Brain, Part 2: Factual Memory](https://www.sentra.app/blog/company-brain-part-2-factual-memory): In the first piece, I argued that a real Company Brain needs three kinds of memory: factual memory, interaction memory, and action memory. Factual memory… - [Company Brain: Why Most Companies Have Data But No Memory](https://www.sentra.app/blog/company-brain-why-most-companies-have-data): One of the hardest parts of any organization is institutional friction. Conversations lose context. Meetings create ambiguous follow-ups. People leave… - [Who Signs? The Anthropic Paradox and the $40 Trillion Choice](https://www.sentra.app/blog/who-signs-the-anthropic-paradox): The augmenting and replacement futures use the same models and the same tools. The thing that separates them is a design choice about where consequence lands. - [The Skeleton of Remembering: Why Your Filesystem Is a Brain Waiting to Happen](https://www.sentra.app/blog/the-skeleton-of-remembering): A designer sees the Golden Gate Bridge and remembers International Orange. An engineer sees cables. A biologist remembers a whale. Same object, three… - [The Price of Meaning: Why RAG, Knowledge Graphs, and Every Semantic Memory Will Always Fail](https://www.sentra.app/blog/the-price-of-meaning): Forgetting and false recall are mathematically, provably, inevitable for any memory system that organises information by meaning. Not just embeddings. Not… - [Geometry of Forgetting: Why Brains and LLMs Fail EXACTLY the Same Way](https://www.sentra.app/blog/geometry-of-forgetting): Memory systems for LLMs forget EXACTLY like humans, reproducing the exact numbers from some of the most replicated experiments in clinical psychology. - [Variance is Not Information: The Shaped Cache Experiment](https://www.sentra.app/blog/variance-is-not-information): After the right rotation, keys need only 1 bit each: just the sign, positive or negative. Key compression is a solved problem. The entire remaining… - [3% Is All You Need: Breaking TurboQuant's Compression Limit via Spectral Structure](https://www.sentra.app/blog/3-percent-is-all-you-need): Only 4 out of 128 dimensions in the KV cache carry meaningful signal. The other 124 are noise. This holds across six models in four families. ## Optional - [Pre-call account brief](https://www.sentra.app/use-cases/sales-pre-call-account-brief) - [What has the CFO said about pricing?](https://www.sentra.app/use-cases/sales-cfo-pricing-stance) - [Open opportunities with overdue commitments from our side](https://www.sentra.app/use-cases/sales-overdue-commitments-by-deal) - [Recurring objections across mid-market deals](https://www.sentra.app/use-cases/sales-recurring-objections) - [Accounts with sentiment shift in the last 30 days](https://www.sentra.app/use-cases/cs-sentiment-shift-30d) - [What did we promise this customer that never shipped?](https://www.sentra.app/use-cases/cs-promises-vs-delivered) - [Six-month handoff brief](https://www.sentra.app/use-cases/cs-six-month-handoff) - [Renewals at risk and why](https://www.sentra.app/use-cases/cs-renewals-at-risk) - [Top customer pain themes this quarter](https://www.sentra.app/use-cases/product-pain-themes) - [What did we decide about the auth refactor?](https://www.sentra.app/use-cases/product-auth-refactor-decisions) - [Where are two teams making conflicting decisions?](https://www.sentra.app/use-cases/product-conflicting-decisions) - [Reconstruct yesterday's incident](https://www.sentra.app/use-cases/eng-incident-timeline) - [Who owns this service and what should I know?](https://www.sentra.app/use-cases/eng-service-ownership) - [Has this design pattern been debated before?](https://www.sentra.app/use-cases/eng-design-pattern-debate) - [Sprint blockers and how they were resolved](https://www.sentra.app/use-cases/eng-sprint-blockers) - [Picture of the company this week](https://www.sentra.app/use-cases/exec-company-picture) - [Strategic initiatives that lost momentum this month](https://www.sentra.app/use-cases/exec-initiatives-losing-momentum) - [Draft a board package for the quarter](https://www.sentra.app/use-cases/exec-board-package) - [Draft a performance review from the work itself](https://www.sentra.app/use-cases/people-performance-review-draft) - [Managers who haven't 1:1'd a report recently](https://www.sentra.app/use-cases/people-1on1-coverage-gaps) - [Promotion packet from the actual work](https://www.sentra.app/use-cases/people-promotion-packet) - [Candidate dossier for the next interview loop](https://www.sentra.app/use-cases/recruiting-candidate-dossier) - [Per-interviewer stance across the loop](https://www.sentra.app/use-cases/recruiting-interviewer-stance) - [New-hire glossary for week one](https://www.sentra.app/use-cases/recruiting-new-hire-glossary) - [What the org thinks about this vendor up for renewal](https://www.sentra.app/use-cases/finance-vendor-renewal-sentiment) - [Verbal commitments that conflict with the contract draft](https://www.sentra.app/use-cases/finance-verbal-vs-written-commitment-diff) - [Contracts auto-renewing in the next 60 days](https://www.sentra.app/use-cases/finance-auto-renewing-contracts) - [Language our best customers actually use](https://www.sentra.app/use-cases/marketing-customer-language-library) - [Draft a case study from the actual interactions](https://www.sentra.app/use-cases/marketing-case-study-draft) - [Status page](https://status.sentra.app): Real-time API availability. - [Contact](https://www.sentra.app/contact): Support, integration questions, security disclosures. - [Sitemap](https://www.sentra.app/sitemap.xml)