One production agent. One painful workflow. 90 days.
We pick the single highest-cost manual workflow in your operation, build a production AI agent that runs it, and deploy it inside your stack — in 90 days, at a fixed price between $50,000–$150,000. Not a pilot. Not a demo. A system doing the work.
You don’t need an AI strategy. You need one agent that works.
Most companies trying to “do AI” overscope it into a transformation program that never ships, or hand it to a vendor whose demo falls apart the moment real data hits it. Both end the same way: months gone, nothing in production.
There’s a faster path. Pick one workflow that’s eating real hours or real dollars — support triage, document processing, intake, reconciliation — and put a single production agent on it. Prove it works under load. Then expand. That’s how the AI-native companies actually got to production, and it’s exactly what a First Agent Deployment does.
A working agent, in your stack, in 90 days.
A scoped, high-ROI workflow
We don't guess — we find the workflow where an agent returns the most, fastest.
A production-grade AI agent
Built with the right model for the job, integrated with your tools, with error handling, guardrails, and fallbacks.
Evals before deploy
We prove the agent works against real cases before it touches production — and give you the eval suite so you can trust it.
Observability from day one
You can see what the agent is doing, where it's confident, and where it escalates to a human.
A clean handoff — or an Operate retainer
You own the code and the system. If you want us to keep running it, that's Managed AI Operations.
Fixed scope. Fixed price. Fixed timeline.
One fixed price for the whole thing. No hourly meters, no scope-creep invoices.
Scope & design
We map the workflow, agree the success metric, and design the agent. Often this is the output of an AI Transformation Sprint.
Build
An embedded pod builds the agent in your stack. Weekly demos. Evals as we go.
Deploy & validate
Ship to production, validate against the success metric, instrument monitoring, hand over the eval suite and docs.
The workflows that pay back fastest
If a workflow is high-volume, rules-heavy, and currently done by a person reading and typing — it's a candidate.
SaaS & Tech
Support copilots, ticket triage, churn-signal detection, onboarding agents, internal ops agents.
Healthcare
Patient intake agents, clinical document summarization, prior-authorization automation, scheduling and reminders.
Cross-industry
Document processing, data extraction and reconciliation, RAG over internal knowledge, voice agents for the front desk.
Production AI is engineering, not prompting.
A demo agent takes an afternoon. A production agent that survives real load, edge cases, and a model-provider price change takes engineering: evals, structured outputs, guardrails, fallbacks, observability, version-controlled prompts.
We’re not a chatbot shop. We don’t ship a wrapper around an API and call it an agent. We build the system and the MLOps that keeps it reliable.
Depending on workflow complexity and integration surface, delivered in about 90 days. Not sure where you’d land? A scoping call gives you the number — or start with a $25,000 AI Transformation Sprint and credit it toward the build.
One workflow, one agent, in production.
AI Support Agent — SaaS
A support agent that resolves 64% of tickets autonomously. $218K saved per year. CSAT up from 3.9 to 4.5. One workflow, one agent, in production.
E-Commerce Ops Automation
Five automated workflows on n8n. 32 hours/week recovered. Inventory accuracy from 94% to 99%.
First Agent Deployment, answered
What is a First Agent Deployment?
A fixed-fee, 90-day engagement where Gigabit builds and deploys one production AI agent for a single high-value workflow — scoped, built in your stack, validated against a success metric, and handed over with monitoring and an eval suite. It costs $50,000–$150,000.
How is this different from a pilot?
A pilot proves an idea in a sandbox. A First Agent Deployment ships a working agent into production, validated against a real metric, with the observability and guardrails to run on live data. You end with a system doing the work, not a slide saying it could.
What does it cost and how long does it take?
$50,000–$150,000, fixed, over about 90 days, depending on workflow complexity and how many systems the agent integrates with.
Do we own the agent?
Yes. The code lives in your repositories and the system runs on your infrastructure. You can run it yourself or retain us via Managed AI Operations to keep it healthy.
What if we don't know which workflow to start with?
That's what the AI Transformation Sprint is for — a two-week diagnostic that ends with a scoped, ready-to-build agent. Its fee credits toward the deployment.
Tell us your most painful workflow.
A scoping call gives you the workflow, the success metric, and the fixed number — or start with a Sprint and credit it toward the build.