Just specify for your team
It's not a stronger AI that changes how you work — it's an AI that knows your team.
Specify gathers your scattered docs, conversations, decisions, and code context into one place, suggests what you can turn into AX (AI transformation) first, and lets an agent team handle the work you agree on. Results flow back into the workspace as context for the next decision.
Work got faster, but context got scattered
Teams re-explain the same background to AI over and over. Docs live here, decisions there, code context somewhere else — and the 'why' that matters most is never written down.
Context in one place, AI as a teammate
Specify gathers scattered docs, conversations, decisions, and code context into workspace memory that people and AI share. Here, AI isn't just a tool — it's a teammate that understands the same context and takes work off your plate.
What you get
Organize knowledge, surface AX, and automate the work
Specify adds value in three steps: it keeps your scattered knowledge optimized, suggests what you can turn into AX (AI transformation) on top of it, and automates the actions you agree on.
Optimize & maintain team knowledge
Pulls docs, decisions, and code context into one place and keeps it current — cutting the cost of upkeep.
Surface AX opportunities
On top of organized knowledge, it suggests what you can automate or move to AI first.
Automate AX actions
Work you agree on runs in the background, with results left in your workspace.
With Specify MCP, your coding agents explore team knowledge
Business context changes every day, and good product work starts from reading it accurately. Specify becomes your central knowledge base so Claude Code, Codex, and local agents can explore personal and team knowledge directly over MCP — no need to switch agents; they just pull in the same context.
Specify becomes the shared knowledge hub for your people and agents.
Works with your agents
Claude Code
Your terminal coding agent references team context.
Codex
Connects to the same knowledge base over MCP.
Local agents
Safely explore personal and team knowledge.
Teams where engineering and product move together
Tech leads & engineering leaders
Teams that want code, docs, and decision context in one place — so they don't re-explain the same background to every new teammate.
Product & operations
Teams that want progress scattered across Notion, Slack, Linear, and Jira in one place — and want AX (AI transformation) candidates surfaced first.
Why Specify
Plenty of tools do similar things — none sit in the same spot
Every AI tool has different strengths. Specify is different in that it works across your team's docs and code context — and surfaces what to turn into AX (AI transformation) on top of it, first.
Platforms where you build the agent
Other approachesPowerful, but your team has to design and set it up.
SpecifyAn agent team is ready the moment you sign up.
Company-wide search
Other approachesFinds scattered answers, but can't co-write and edit the docs with you.
SpecifySearch and real-time co-editing live in one workspace.
Code-only agents
Other approachesThey write the code, but don't know your team's decisions and doc context.
SpecifyReads team knowledge on top of the same code context — and hands that context to your agent.
A hand-built LLM wiki (Obsidian · Claude Code)
Other approachesYou design the raw/wiki structure and write the upkeep scripts yourself.
SpecifyConnectors gather it automatically, and AX Scout finds what's stale first — shared across the team.
Control always stays with your team
Only within what you allow
Agents access only the tools and data your team connects and permits.
Every result is recorded
What an agent does stays in workspace docs and edit history, reviewable anytime.
Fabricated citations are auto-demoted
If a source marker in an answer doesn't match a real reference, it's automatically demoted to plain text — so nothing looks cited when it isn't.
Isolated per workspace
Data is protected by membership and permissions, and search itself is scoped per workspace — so another team's data never even enters the candidate set.
Start working with AI today
The workspace where people and AI agents work on the same shared context.