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The Agentic AI Stack
Emenanjo Ndigwe · Aug 7, 2026 · 8 min
Modern AI agents are more powerful when they can move beyond conversation. A model that can only reply in a chat window is a very well-read intern with no hands. The tools in this session are what give it hands: live web data, real browser interfaces, secure execution environments, document understanding, and access to external applications. Wire enough of them together and an agent stops answering questions and starts finishing tasks.
The Pipeline
Five moves from talk to action
Every agentic workflow we've tested at TEKHUB reduces to some combination of five moves. Knowing which move a tool covers makes it much easier to figure out what's actually missing from your stack.
None of these are optional if you want an agent that does real work. A model that can discover and capture but never act is a research assistant. One that can act but never discover is dangerous. The interesting products combine at least three of the five.
The Directory
The ten tools behind it
These are the platforms currently doing the heavy lifting across the agentic stack — the ones worth knowing by name before you evaluate a vendor pitch that's really just a wrapper around one of them.
Composio
ActConnects AI agents to external apps and tools while handling authentication, tool discovery and secure execution — the part of the stack most demos skip because OAuth and permission scopes aren't as fun to show off as a chat reply.
Tavily
DiscoverSearch infrastructure built for AI agents, returning live web results and research context that can ground model responses — what stops an agent from confidently answering with last year's facts.
Exa
DiscoverAn AI-native search and retrieval API for finding high-relevance pages, documents and web content. Where Tavily leans toward grounding a live answer, Exa leans toward finding the right source in the first place.
Apify
CaptureRuns cloud scrapers and automation "Actors" for extracting structured data from websites and web applications at scale — useful when the data you need doesn't have an API and never will.
Firecrawl
CaptureCrawls websites and converts pages into clean, AI-ready Markdown and structured content for agents and RAG pipelines — the difference between "the model read the page" and "the model choked on the cookie banner."
Unstructured
CaptureParses PDFs, Office files and other unstructured documents into cleaner elements for RAG, search and agent workflows. Most real business data still lives in a PDF, not a clean API — this is what makes it usable.
Jina AI
CaptureProvides AI-friendly retrieval infrastructure for turning URLs and web content into cleaner text and searchable context — sits next to Firecrawl in the Capture layer, with its own take on reader and search endpoints.
Browserbase
OperateProvides cloud browser infrastructure so agents can open pages, navigate websites and complete browser-based workflows reliably — the plumbing underneath most "AI that uses a browser" products you've seen demoed.
Browser Use
OperateLets AI agents understand and control browser interfaces so they can click, type, navigate and complete multi-step web tasks. If Browserbase is the browser, this is closer to the hands operating it.
E2B
ComputeGives AI agents isolated cloud sandboxes where generated code can run safely, process files and return computed results — the difference between a model that writes code and one that can actually run it and check its own work.
Takeaway
The real advantage isn't in any one tool
The advantage is not in using one tool. It is in orchestrating several of them so AI can discover information, understand it, compute on it and trigger real outcomes. A single API from this list is a feature. Three or four of them, chained together with clear permissions and a task worth finishing, is an agent that actually earns the name.