Build your agents, workflows, skills, and memory once — then point them at whatever model is best this week, no rewrites. One quiet workspace where chat, tools, data, and every model share the same context and the same keystrokes. Cloud or local.
Explore probabilistically. Ship deterministically. The path your model figured out in chat becomes a repeatable workflow — same answer, every time, at a fraction of the cost.
The workflows you ship come out of the chats that worked. Go back and forth in chat — running code, calling tools, trying models — until you have the answer, then say "save this and run it every morning." Catalyst turns that working sequence into a workflow it can repeat exactly.
Workflows automate the work; mini apps give that work a face. Describe the little tool you want — "an app to log my food and chart it" — and Catalyst builds the workflows behind it, writes the app, and opens it live in your chat. A real, working tool, generated on request, with no front-end to build.
Catalyst is a real workspace, not a thin shell over someone else's chatbot. Every surface — chat, workflows, mini apps, collections, agents, MCP, memory, data — shares the same models, the same context, the same keystrokes.
A new state‑of‑the‑art model ships every few weeks. The price floor drops every few months. Build your agents, workflows, skills, and memory in Catalyst once — then point them at whatever's cheapest and smartest today, tomorrow, and the month after that. Build the work; swap the model.
Switch between any model, watch it reason step by step, read images and PDFs, render math and diagrams, run code, generate images — and a toolbar that grows as you connect more tools.
Connect servers running locally or in the cloud — secure sign‑in is handled for you. Catalyst finds each server's tools automatically, and they work everywhere: chat, workflows, and agents.
Postgres, MySQL, Oracle, or anything on your private network. Drop live values straight into your queries, with results cached for speed. Never copy‑paste a spreadsheet again.
SELECT * FROM revenue WHERE q = {{ quarter }} AND plan IN {{ plans }} A collection is a named bucket of your own data — no schema to design, no tables to set up. Workflows fill it, mini apps surface it, chat queries it. It's the shared layer that makes "log my food, then chart it" work end to end — one source of truth across a workflow, an app, and a conversation.
It captures facts, session summaries, and your preferences — then brings the relevant ones back exactly when they matter. It searches by meaning, runs locally or in the cloud, and nothing leaves your control.
CRO prioritizes net retention over new logo growth through FY26.
Board agreed to defer mid‑market hiring until pipeline coverage exceeds 3.2×.
Enterprise expansion ARR concentrated in top 14 accounts; renewals Q1–Q2 FY26.
Set an agent loose to plan, call tools, and carry out the work. Step through every decision, pause at any point, or stop it instantly.
Bundle instructions, tools, and prompts into named skills your AI can invoke on demand — across chat, workflows, and agents.
The chat that worked becomes a repeatable, scheduled workflow — same answer every time, at a fraction of the cost.
Cheaper, smarter models drop monthly. Swap them like a config — your work stays.
It remembers facts about you and your work, so your AI keeps getting sharper.
Plug in tools, apps, and files — anything that speaks MCP, the open standard for connecting AI.
Models, agents, workflows, data, tools, and memory — in a single, quiet interface.