Tell us the internal process eating the most hours. We run the deep-dive, build the agents, deploy them in your own workspace. You measure the hours back — typically in under two weeks.
Enterprise teams don't have detailed workflow specs — they have people who know how things actually work. Our team runs the deep-dive call, captures the trigger, inputs, steps, edge cases, and success metric, and turns it into a build plan your team didn't have to write.
Standardize error responses across all endpoints.
The current error responses are inconsistent across handlers — need a unified format with error codes.
I've standardized error responses across 14 handlers. Each error now includes a code, message, and request_id. PR #43 is ready for review.
Looking good. Make sure to preserve the existing HTTP status codes — some of our frontend relies on specific codes like 409.
One process, walked end-to-end on a real example. Your engineer drives the questions; we listen, probe judgment points, and capture what's in your team's head.
We don't ask you to write a spec. We extract it on the call by watching the person who actually does the work, then write it up for you to review.
What goes wrong weekly? What's the override path? We probe for exceptions during the call so the agent ships with them already handled.
We build inside your tenant, install connectors with your IT contact, wire the autopilots, and run the first end-to-end test on a real example from your team. You sign off when the agent's output matches what your team would have produced.
Everything runs in your Getdeployed tenant against your data. We deploy and then step out — your prompts, transcripts, and outputs never reach us after handoff.
Gmail, Calendar, Drive, GitHub, Notion, Slack, Recall.ai for meetings — we install the OAuth, pin them to the right agents, and document who owns the renewal.
Before sign-off, we run your last real instance through the agent. If the output isn't what your team would have produced, we don't ship.
Agents live in your workspace, run on your runtime, and stay editable by your team after we leave. No platform lock-in, no required ongoing services contract — the build is a one-time engagement, the agents are an asset on your books.
Write Migration
Generate a SQL migration file based on the requested schema changes. Validates against the current database state and generates both up and down migrations.
Steps
Agent runtime, connectors, issue tracker — every layer of what we deploy is open source. Inspect the code, self-host the whole stack, fork it.
Each agent is plain-text instructions plus a list of connector pins. Your engineers can read them, edit them, and re-deploy without coordinating with us.
Pay for the build, walk away with running agents. Keep us on for workflow #2 if you want — most customers do, but it's optional, not contractual.
The first build is the proof. Every workflow after that ships faster: we reuse the connectors you already installed, the agent patterns your team already approved, and the autopilot infrastructure that's already running.
Each agent ships with skills your next agent can lift. Build #1 lays the foundation; build #5 is half the work because the plumbing is already there.
Some workflows need 2-3 agents handing off (triage → respond → log). We compose them as squads with explicit responsibilities, not one mega-prompt that gets brittle.
Agents fire on a schedule, on an email, on a webhook — no one has to open a chat window. The hours back are real work the team doesn't have to do, not faster typing.
How we work together
We walk one of your most painful internal workflows end-to-end with the team that does it today. You don't prepare anything — we drive the questions, capture the trigger, inputs, steps, edge cases, and success metric live.
Within 48 hours we send back a structured spec: agent playbook, required connectors, exception branches, success metric. You confirm it matches reality before any code gets written.
We set up your Getdeployed tenant, install connectors with your IT contact, wire the agents and autopilots, and run the first end-to-end test on a real example from your team.
We measure hours saved against your baseline. If the agent hits the metric, we plan workflow #2. If it doesn't, we iterate or refund — your call.
Open source
Getdeployed is fully open source. We deploy the agents in your tenant, against your connector tokens, on your LLM provider account — then step out. Inspect every line of the platform you're running.
Run the platform on your own infrastructure: Docker Compose, single binary, or Kubernetes. Your tenant, your network — we never see what your agents see.
Agent prompts, transcripts, action items, generated reports — all stored in your workspace. We don't have read access after we hand off.
Inspect every prompt the agent sent, every tool call it made, every output it produced. No black-box decisions, no model-behind-the-curtain.
Bring your own LLM provider, swap connectors, extend the API. The agents we ship are yours to fork, retire, or rewrite without coordinating with us.
FAQ
Any internal process where your team is moving information by hand: email triage, daily sync reports pulled from multiple sources, meeting summaries with action items, vendor onboarding, procurement deep-dives, contract clause comparison, customer support routing. If it has a trigger, inputs, steps, and a 'done' state, we can build it.
First call to deployed agent is under two weeks per workflow. Discovery ~30 min, spec for your review ~48 hours, build + first end-to-end test ~5 days, ROI checkpoint at week 2. Subsequent workflows ship faster because the connectors and patterns are already in place.
One-time build fee per workflow, scaled to complexity. The platform itself is open source — you only pay for the build engagement plus your own LLM provider and connector usage. No platform license, no monthly seat fee. Book a session for a scoped quote.
The agent runs in your Getdeployed workspace, against your connector OAuth tokens, on your LLM provider account. We set it up and then step out — data flows directly between your tools and the LLM. We don't see prompts, transcripts, or outputs after handoff.
Yes — that's the design. Each agent is plain-text instructions plus a list of connector pins. Your team can read, edit, fork, or retire any agent without coordinating with us. Most customers keep us on for workflow #2, but it's optional, not contractual.
Agent instructions are markdown — your team edits them like a doc and re-deploys. For bigger shifts (new connector, new exception branch) we run a follow-up build session. The plumbing we set up the first time doesn't have to be redone.