Announcing our $13M seed to put AI Agents in the hands of every team (code or no-code).
So far, we've worked with top companies like Anthropic, Midjourney, Clay, PostHog and tons more to power their customer-facing AI assistants.
Today, we’re launching Inkeep Agents: a platform where both business and engineering teams can build AI agents together.
Our story 👇🧵
Missed our latest webinar with @composio?
We walked through how to give AI agents access to 15,000+ tools using Inkeep + Composio MCP serverswithout building integrations from scratch.
⚡ Live demos connecting agents to Slack, GitHub, and Gmail
🧠 Best practices for production-ready agent integrations
Watch the recording 👇
https://t.co/T9UfCfuYDc
🚨 Happening this Thursday
If you’re building AI agents that need to connect to real-world tools- this is for you.
This Thursday, we’re going live with Inkeep + @composio to show how you can give AI agents access to 10,000+ integrations without maintaining brittle, one-off connections.
🗓 Feb 26
⏰ 10:00 AM PST
💬 RSVP in the comments
What you’ll learn:
• How Inkeep’s AI agent framework handles tool use and agentic workflows
• Why integrations are critical for production-grade AI agents
• How Composio’s MCP servers unlock 10,000+ tools out of the box
• Live demo: connecting agents to Slack, GitHub, and Gmail
• Best practices for auth, testing, and deploying agent integrations in production
Speakers:
🎤Omar Gonzalez — Founding Engineer, Inkeep
🎤 Jayesh Sharma — AI Engineer, Composio
🎤 @gauravnvarma — DevEx Engineer, Inkeep (Moderator)
If you're serious about shipping real-world agents- don’t miss this.
👇 RSVP in the comments
🌟 Excited to see @descopeinc's Docs MCP Server live!
AI-powered IDEs are quickly becoming the default way developers build. Making product knowledge directly accessible inside those workflows is a big step forward, which is why we built an MCP of our own to help you 'vibe code' agents using our agents SDK (link in the comments).
We’re proud that Inkeep is powering key under-the-hood components of Descope's MCP server with semantic search and RAG.
Congrats to the Descope team on the launch 👏
🚀 Introducing the @descopeinc Docs MCP Server
If you’re using AI-powered IDEs (who isn’t?), you now have an easy way to add auth to your apps and reference Descope product knowledge.
🧵👇
We think "Agent Engineer" is becoming a real role.
After hundreds of hours building AI agents, we've condensed what we've learned into a new guide:
• How to structure prompts that actually work
• Troubleshooting when agents fail
• Coordinating multiple specialists
Not theory. Battle-tested techniques. Link in the comments below.
🚀 Webinar: Connecting AI agents to 15,000+ real-world tools- without painful integrations with Inkeep and Composio
AI agents are only as powerful as the tools they can use. But connecting agents to CRMs, productivity tools, databases, and APIs often means maintaining dozens (or hundreds) of brittle integrations.
In this webinar, engineers from Inkeep and Composio will show how you can give AI agents instant access to 15,000+ tools using Composio’s MCP server library- without building integrations from scratch.
🗓 Feb 26
⏰ 10:00 AM PST
💬 RSVP in the comments
What you’ll learn:
• How Inkeep’s AI agent framework handles tool use and agentic workflows
• Why integrations are critical for production-grade AI agents
• How Composio’s MCP servers unlock 15,000+ tools out of the box
• Live demo: connecting agents to Slack, GitHub, and Gmail
• Best practices for auth, testing, and deploying agent integrations in production
Speakers:
🎤 Omar Gonzalez — Founding Engineer, Inkeep
🎤 Jayesh Sharma — AI Engineer, Composio
🎤 Gaurav Varma — DevEx Engineer, Inkeep (Moderator)
If you’re building real-world AI agents (or want to), this one’s for you.
👇 RSVP in the comments
Agent skills are powerful- but most are built wrong.
In this video, we show how to generate always-up-to-date https://t.co/ol5oMrN53s files directly from your docs with automated GitHub workflows.
Built for Claude Code, Codex, and Cursor.
AI can chat with citations and semantic search transforms support tickets into prioritized feature requests for your product roadmap.
In this blog, we explore AI support's impact no product roadmaps: extracting insights from Support data.
Key Takeaways:
- Support tickets contain roadmap intelligence—most teams never extract it.
- Citations are non-negotiable: PMs won't prioritize unverifiable AI suggestions.
- Semantic clustering reveals patterns keyword search completely misses.
- Start with one channel, validate citation accuracy, then expand coverage.
- 40% of AI support implementations fail from lack of grounding.
Learn more in our blog post in comments.
🚨 Webinar reminder: happening next Wednesday 🚨
Debugging AI agents in production is still way harder than it should be.
Non-determinism, unpredictable latency, and rising token costs break most traditional observability workflows- especially once agents start calling tools and chaining reasoning steps.
That’s exactly what we’ll dig into in @inkeep × @SignozHQ's live webinar on Debugging AI Agents: Observability Best Practices.
You’ll see how teams:
- Trace end-to-end agent execution
- Inspect tool calls and decision paths
- Monitor latency and token usage in real time
- Debug failures without guessing
🎤 Speakers & Moderators
- Shagun Singh — Software Engineer @ Inkeep
- Goutham Karthi — Software Engineer @ SigNoz
- @anush_karma — PMM @ SigNoz
- @gauravnvarma — DX Engineer @ Inkeep
📅 Jan 28 | ⏰ 11:30–12:10 PM PT | 📍 Zoom
⏳ We’re just a week out- event link in the comments 👇
If you're adding AI chat to your developer docs: don't start with the chatbot.
Start with the retrieval layer. We've seen DevTools companies reduce support tickets by 40%+ after adding RAG-grounded chat to their docs.
We write more on this here in our blog (link in comments)
Build AI support in-house or buy? We wrote a guide that provides a decision framework, ROI comparison, and scorecard for evaluating low-code + SDK platforms.
Key Takeaways
- Hybrid platforms eliminate the speed-versus-customization tradeoff entirely.
- 65% of software costs hit post-deployment—your 3-month build becomes 9 months.
- Two-way code-UI sync prevents ops and dev teams from fragmenting.
- Context failures—not model failures—kill most production AI deployments.
- If you can't version control agent behavior, you can't safely iterate.
Link in comments for latest article.
Enterprise leaders need 4 AI support capabilities by 2026: indexed product chat, inline citations, guardrails, and semantic search.
Key Takeaways
- Purpose-built AI deflects 85% of queries—generic tools hallucinate under pressure.
- Citations aren't optional—technical users verify before implementing anything.
- Skip knowledge indexing and your AI confidently delivers wrong answers.
- By 2027, 80% of critical AI decisions require human oversight dashboards.
- Implementation sequence matters: foundation first, chatbot second, search third.
Read more on our blog, link to comments.