The missing operating layer for AI work. Structured workflows, checkpoints the AI cannot skip, and memory that survives across sessions — running inside Claude, ChatGPT, Cursor, or whatever comes next.
Ready-made processes. Start in minutes.
Every tool your AI can call through ConvOps.
Every action logged — who, what, when.
ConvOps puts your real process inside the AI conversation. Define workflows, create tasks, and let the AI drive — step by step, checkpoint by checkpoint.
One MCP connection to Claude, ChatGPT, Cursor, or any AI that supports tools. After that, every future conversation is process-aware.
mcp.convops.appNo builder. No config screen. Describe your process in the chat. ConvOps saves it as a reusable workflow — with steps, instructions, gates, and rules for which tasks it auto-attaches to.
Saved Create Blog Post to your workspace. It will auto-attach to any content task tagged blog.
Research the topic, identify key points, create a structured outline.
Tell your AI to use ConvOps for work requests. The AI will create tasks, pick up the right workflow, and follow it step by step — without you managing anything.
Use ConvOps for any work request. Create a task and follow the workflow.
Employee asks for work. The AI creates a task, the right workflow auto-attaches, and the AI drives through it — following each step's instructions, asking for input, pausing at gates. You just respond.
Created "Q2 Launch Blog Post". The workflow attached automatically. Starting Step 1.
What's the launch date, and what are the three biggest differentiators I should lead with?
Draft is ready. Editor review is a gate — I'm pausing here until you approve.
ConvOps gives you a dashboard with every task, its workflow stage, who did what, and a full audit trail. Like Jira — but AI-first, where the conversations are the work.
The AI drives. You respond. Your workflow guides the AI underneath — step by step, checkpoint by checkpoint, across any AI your team uses. The AI drives. You respond.
Chat tools help people talk to AI. ConvOps structures the work happening inside those conversations — so teams get consistency, continuity, and governance as usage scales.
Workflows define the path. Each step injects only the instructions it needs, exactly when the AI reaches it — not a 40-page master prompt the AI stops reading halfway through.
Approvals, dependencies, and checkpoints are structural rules the AI cannot improvise around. The workflow engine enforces them — no prompt trick can skip a gate.
Legal review is a gate. I've completed the draft, but I cannot proceed until you explicitly approve. This is enforced by the workflow — not a suggestion.
Agents should not need long routing instructions that say which task to create for every kind of request. ConvOps can read the work request, choose the correct task path, and start the workflow that belongs there.
"Review the new vendor DPA before signature."
The agent says the work naturally. ConvOps picks the task path. The right workflow attaches automatically.
Explore Task ClassificationPolicies let you define behavioral rules once and inject them into the active step exactly when the AI reaches it. No duplicated instructions across templates. No giant prompt blob. Just the right rule, at the right moment.
The template stays clean. The active step gets the rules when it runs.
Explore PoliciesBrain makes the next AI session start inside the way your team works: process known, rules attached, context remembered.
This is the shift: AI work begins as a continuation, not a reset.
Explore ConvOps BrainPick a scenario and watch the workflow guide the conversation to the outcome.
Discuss requirements with the user before planning.
Create architecture and define implementation phases.
Structured review for completeness and correctness.
Run each phase sequentially with implementation agents.
Full acceptance testing against running environment.
Capture context, store learnings, update routes.
Traditional AI chat puts the human in the driver's seat. ConvOps inverts the operating model.
Claude, ChatGPT, Cursor, Copilot — it doesn't matter which AI your team picks. Every conversation follows your process, shares the same memory, and produces the same audit trail.
Write a blog post about our Q2 product launch.
Created "Q2 Launch Blog Post." The workflow says to start with research — what's the launch date and the three biggest differentiators?
July 8. Governance, resumability, vendor flexibility.
Draft is ready — 1,480 words, 5 sections. This step requires your approval before I can continue.
Looks good. Approved.
Formatting for CMS, adding meta description and three internal links.
Blog post is live. All 4 steps done.
Following the approved outline. Drafting section 1 of 5 — introduction and market context.
Keep the intro under 200 words. Lead with the problem.
Noted. Rewriting with a concise problem-first opening.
Every conversation follows your defined process.
Close the tab. Come back tomorrow. The AI picks up mid-step.
Same workflow, same quality — across any AI, any team member.
The AI does not decide whether to honor these. The workflow engine enforces them — every step, every time, with a full audit trail.
The AI asks: "Draft is ready. Approve to continue?"
It will not advance until you respond.
The AI asks you to approve before advancing to the next step. It will not move on its own — the workflow pauses until you explicitly say "yes." No prompt trick can bypass this.
Parent work cannot advance until all required sub-tasks are complete.
A plan cannot close until every phase has reached the required state.
A step only runs when the task is in the expected lifecycle state — like "review" or "ready."
Workflows enforce that only the right kind of work enters a given step.
The step blocks until all listed dependencies are done first.
Children execute one after another in strict order — no parallel drift.
Long master prompts dilute focus. ConvOps delivers instructions exactly when the workflow reaches that step.
The difference is not cosmetic. It is a different operating model.
| Feature | ConvOps | CLAUDE.md / Cursor Rules | Custom GPTs / Projects | Notion playbooks |
|---|---|---|---|---|
| Step-at-a-time injection | ✗ (one static blob) | |||
| Enforced gates the model cannot skip | ||||
| State across sessions | partial | |||
| Works across AI vendors | ✗ (per-tool) | ✗ (vendor-locked) | N/A | |
| Auditable per-step log |
The objections buyers raise most often, answered directly.
Replace system prompts and playbooks with structured workflows. Works inside Claude, ChatGPT, Cursor, and more.