The one place to build, deploy and run AI agents — embedded in your product, working autonomously in the background, or sitting next to your team as named AI assistants.
Experiment in minutes, scale to millions, enterprise guardrails baked in.
Three ways to put a CatalEx agent to work — embedded in your product, talked to in plain language, or hired as a virtual employee on your team.
CatalEx agents run inside the product your customers already use, connected through simple APIs. Your engineers ship agents into the user experience without rebuilding it.
Set the goal, define the guardrails, walk away. CatalEx agents handle the long-running work — quietly, on schedule, until it's done.
Hire an AI assistant by name and role. They live in the tools your team already uses, learn how each person works, and turn every employee into the lead of their own AI.
Every person on your team gets their own AI assistants — pick from a library of pre-built roles, or shape your own. They live in the tools you already use, learn the way you actually work, and pick up where you left off.
Analyst, SDR, support, ops, researcher, recruiter, and more — each one shaped by best practices for the role. Or define a new one in plain language.
Your assistants watch how you write, decide, escalate, and close the loop. They sound like you, and act like a teammate who's been at your side for years. They keep learning as your business and your work evolve — supercharging every person's personal productivity.
They watch for signals across your knowledge and tools and step in before being asked. Every action runs inside guardrails you set — what they can do, what they need approval for, what they can never touch.
"Ticket volume spiked 38% after yesterday's release. I've drafted a postmortem outline — share it with the team?"
Most teams either never run the experiments to find what's worth building, or they build something that was never engineered to survive real users. CatalEx packages the experimentation runtime and the production runtime — so the hard parts are handled and tech quietly disappears.
Most agents are built like demos — in notebooks, with hand-wired plumbing — and they break the moment they meet real traffic. CatalEx agents are engineered to ship to production from day one.
Teams get stuck on one bet when they should be running ten. CatalEx makes experimentation cheap and fast, so you can throw out what doesn't work and double down on what does.
Every agent carries its own context. No amnesiac restarts.
Agents catch their own mistakes mid-run and course-correct.
Each agent reads its purpose and tracks what matters — claim pass rate, deflection, conversion. Change in chat.
Every agent in its own protected environment. No shared state, no collateral damage.
One agent or ten thousand. Concurrent, isolated, no babysitting.
We cache the code your agents write, re-run it with new parameters, and route each action to the right model. Up to 10× lower token cost on typical workloads.
Industry data points. Your numbers will vary — happy to walk through ours.
CatalEx is built for teams whose agents touch regulated data, customer money, or production systems. Every guardrail you'd build yourself, already in the platform.
Every agent, every action, scoped to who's allowed to see and do what. Permissions inherited from your existing identity provider.
Every decision, every tool call, every approval — recorded, timestamped, and queryable. Your auditors will thank you.
Deploy in your cloud, your region, your VPC. Your data never leaves your perimeter — and never trains anything.
Define the actions that need approval, the ones that can run free, and the ones that can never happen. Agents wait, humans confirm.
Work used to require people at every step — directing, executing, evaluating. In the new world, AI handles the execution. People direct. People review. Your company becomes AI-native.
Smaller teams. Greater leverage. Same ambition — exponential output.
To automate execution, you need three things: Intelligence, Memory, and Orchestration. The intelligence layer is already here. CatalEx builds the rest.
Data flows in from your tools — docs, conversations, code, tasks — and gets indexed into a unified knowledge graph.
The Memory layer stores context about your org — who works on what, what was decided, where things stand.
Intelligence layer uses frontier LLMs to understand, synthesize, and generate — grounded in your company's context.
Orchestration connects to your tools via MCP agents and drives tasks to completion autonomously.
We are in the Memory phase — building the knowledge layer that powers everything else.
Docs, Sheets, Slides
Channels and threads
Repos, PRs, issues
Projects and sprints
Wikis and databases
Spaces and pages
Four phases from assisted knowledge to fully autonomous work.
Build company knowledge
CatalEx indexes your documents, conversations, and tools into a unified knowledge graph. Your company's collective memory becomes searchable, cited, and actionable.
AI does the work after you decide
Meetings end and tasks get done. People become reviewers — they take their hands off execution. The system connects to tools via MCP and drives work to completion.
Work runs on a schedule
Users schedule recurring workflows. AI picks up signals of work — a Slack message, a calendar event, a status change — and executes without being asked.
Every person gets an army
The system extracts work for you. Specialized agents — HR, engineering, sales, ops — pick up tasks and execute end-to-end. Every person operates with the leverage of an entire team.