toolscaled.

business processes, captured and replayed

Spend your time running
your business —
not learning tools.

Captured workflows, not improvised prompts.

Complete a process with an agent. Export it as a deterministic workflow. From then on it runs on its own — no AI in the loop.

It talks to the systems your business already uses, fires on a schedule or a webhook, and pauses for a human when one is needed. Every run produces the same result.

Get early access Open the app →

See it run.

Describe the problem in chat — the agent figures out the wiring. Capture it as a deterministic workflow. Watch the trigger replay it — same result, every run.

chat — just describe it Each morning, email me a report on my watchlist On it — pulling quotes and last night's filings ⋯ Done ✓ — your report is in your inbox. Perfect — do that every morning at 7. ✓ captured as a workflow ⏰ 07:00 · daily get_watchlist() get_quote({ticker}) for each — ×3 tickers summarize_filings() per ticker · ×3 send_email(report) 📩 report delivered ✓ same result — every run 01 · CHAT — describe the problem. The agent does the work. 02 · CAPTURE — the agent wired it up. Here's the workflow it built. 03 · RUN — 07:00 fires, the graph replays. No AI in the loop. Every run: complete · correct · consistent — same result, every time chat — just describe it When someone posts in #support, look up their order and draft a reply On it — trying it on the last post, from Dana ⋯ Done ✓ — replied in the thread with order status. Great — handle every new post like that. ✓ captured as a workflow 💬 #support · new post lookup_customer({sender}) get_orders({customer}) status · shipping past_tickets({customer}) history · context reply_in_thread(draft) unsure? → human review 💬 reply posted in the thread ✓ every post, handled the same way 01 · CHAT — describe the problem. The agent does the work. 02 · CAPTURE — the agent wired it up. Here's the workflow it built. 03 · RUN — a customer posts. The same playbook replays. Every post: complete · correct · consistent — reviewed when unsure chat — just describe it Can you answer support emails? Check the order, our docs, then reply. On it — trying the latest email, from Dana ⋯ Done ✓ — drafted from the order + policy, replied. Great — handle every email like that — flag any you're unsure of. ✓ captured — unsure ones wait for your approval. 📧 new email · support@ lookup_customer({sender}) classify_issue({body}) ✦ get_orders({customer}) kb_search({issue}) draft_reply(order · kb) cites the order & the policy send_reply({thread}) ⏸ human review confident ✓ unsure 📧 replied in the customer's thread ✓ ✓ edge case — approved by a person, then sent 01 · CHAT — describe the problem. The agent does the work. 02 · CAPTURE — the agent wired it up. Here's the workflow it built. 03 · RUN — an email arrives. The same playbook replays. When it's unsure, it pauses for a person — approve, and it sends.

Works in the chat you already use

Claude Desktop · ChatGPT · Cursor · any MCP client · our app

toolscaled is bidirectional MCP. Build, capture, run, and observe from the chat you're already in — or use ours. Same workflows, same triggers, same runs.

how is this different

Three ways people automate today.
None of them work for the people who know the work.

vs. drag-and-drop builders

Zapier · Make · n8n · Airplane · Retool

Same plumbing quality. But they make you specify the workflow upfront on a canvas, before you've actually run it. We let you discover the right shape by running it in chat — and capture the artifact after the process has been verified to work.

vs. scripts and code pipelines

Python jobs · cron + bash · Dagster · Airflow · Prefect

You can absolutely write the script. Most people don't — because the person who knows the work isn't the person who writes the code. We remove the translation step. The expert captures the workflow directly from chat. No engineer in the middle, no Jira ticket, no spec drift.

vs. AI scheduled tasks

Claude Routines · ChatGPT tasks · Perplexity Tasks

Those re-execute a prompt every run — the model improvises the plan from scratch each time. Same task, different result. We replay a captured workflow: same outputs, every fire, zero orchestration tokens spent figuring out what to do.

how it works

Build. Capture. Run. Observe.

01

Build, in chat.

Talk to your real systems with an agent. Salesforce, GitHub, Stripe, your warehouse — whatever your business already runs on. Iterate until the chat does the job correctly.

02

Capture as a workflow.

Save the working session as a deterministic workflow. The dependency graph builds itself from what the chat actually called. Auditable structured text — not opaque code.

03

Run on a trigger.

Cron, webhook, or a button. One event can fan out to many workflows. Pause for a person when judgment is needed. Built to run unattended.

04

Observe — and fix in chat.

Every run gets a full trace. Health rolls up across the org. When something needs to change, open the workflow in a chat and edit it the way you built it.

Multi-tenant. Role-based access. Full audit trail. Your own model tokens. Bidirectional MCP — runs in Claude Desktop, ChatGPT, Cursor, or our app.

what it feels like

The work done.
Your way.

Tuesday. 8 a.m.

You get up. You make coffee. You open your email.
The morning report is already there. Twelve tickers. Quotes. Ratings. Last night's filings. Ranked the way you said matters.
Nobody wrote it. Nobody scraped it. Nobody pinged you about it overnight.

It just runs.

2 a.m. Your phone wakes you.

It's a P1.
You unlock the screen. The full picture is already on it — the alert, the service status, last night's deploys, the runbook for this exact failure, the two times it happened before, and what fixed it.
Six dashboards. One notification.

You decide. You don't dig.

A customer asks about their last order.

You're mid-conversation. Voice, chat, doesn't matter. The model needs context — fast.
It calls one tool. Order. Warranty. Tickets. Returns. Satisfaction.
Half a second.

The conversation never stalls.

four words. every run.

What you get,
every fire of every workflow.

C

Complete

Every data point the author said matters. Fetched. Every time.

C

Correct

The plan they authored. Not whatever the model improvised this morning.

C

Consistent

Same shape of output. Every fire. No drift.

F

Fast

One deterministic execution. Not an agent feeling its way through a tool catalog at run time.

Get early access

toolscaled is in early access. If you have a process that's repeatable but not yet repeated, we want to talk.

hello@toolscaled.com