AI Agents That Do the Work, Not Just Talk About It.
We design, build, and run AI agents on your real data, and we carry them all the way into production. You get hours back, fewer costly mistakes, and a system your team trusts enough to hand real work to, with a human in the loop wherever it matters.
A Demo Is Easy.
Production Is the Job.
It only works on sample data.
The vibe-coded pilot looked great in a meeting, then fell apart the first time it met your real records, exceptions, and edge cases.
Nobody trusts it enough to use it.
Without checks, reviews, and a clear record of what it did, people double-check everything, and the time savings never come.
Nobody owns keeping it running.
The vendor handed over a prototype and moved on. When something changes, it breaks, and it quietly gets turned off.
3 Kinds of AI Systems, One Way of Building Them.
Whether the agent works in your back office, inside your product, or across your systems, it gets the same senior engineering and the same safeguards.
Agents that run back-office work
Take the repetitive, rules-heavy work off your team so they spend time on judgment calls.
- Order intake and processing
- Document review and data extraction
- RFP and proposal drafting
- Reporting that builds itself
AI inside your product or service
Assistants and features your customers use, built on content you trust.
- Chat assistants on vetted content
- Multi-language support
- Answers that cite their sources
- Safe handling of off-topic questions
Custom platforms and integrations
The software underneath: connecting your tools and giving AI a clean place to work.
- Custom applications and portals
- API integrations between your tools
- Data layers across many systems
- Modernizing legacy software
The Safeguards Come Standard
Every agent we ship includes the pieces that let your team rely on it, not just try it.
Validation on every output
Rules and checks catch bad results before they reach a customer, a report, or your ERP.
Human-in-the-loop
Anything uncertain goes to a person to review. As the agent proves itself, you decide what it handles alone.
Audit logs for every run
Full audit logs show what the agent did, when, and why, so issues are easy to trace and easy to explain.
Runs in your environment
Your data stays in your systems, behind your access controls, with costs and usage you can see.
Swap models anytime
Drag and drop between Claude, OpenAI, and open-source models, so every task gets best-in-class intelligence and sensitive data can stay on models you host.
From Idea to Production, in Weeks
We prove it works first, then make it solid. You see working software every week, not a big reveal at the end.
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01Prove it Start with the riskiest part
A 2-Day POC or a short scoping sprint shows the agent working on your real data before you commit to a full build.
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02Build it with you Weekly releases
We ship working pieces every week and put them in front of the people who will use them, adjusting as we go.
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03Harden it Checks, monitoring, access
We add the safeguards, connect it to your systems, and make sure it holds up on a busy day.
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04Hand it over or run it Your choice
You get the code, documentation, and training. Keep us on to run and improve it, or take it in-house.
Agents Already Running in Production
From failed vendor to live product in 30 days
We rebuilt a medically certified patient chatbot for We CU and Novartis as a team of specialized agents: answering questions, staying on topic, translating, and reading uploaded documents.
An AI coach that keeps new hires past day 60
For Ditech, an agent coaches every new hire proactively, tracks their milestones, and flags who needs support, so supervisors step in before people walk out.
Everything You Need to Own It
No black boxes and no lock-in. The system is yours, and so is everything needed to run it.
Agents running in production. Live on your data, connected to your systems, used by your team.
The source code. In your repository, in your environment, from day one.
Documentation and runbooks. How it works, how to fix common issues, and how to change it.
Monitoring you can read. A simple view of what the agent is doing, how often it needs help, and what it costs.
A trained team. The people who use it and the people who maintain it both know how.
Before You Ask
The questions operators, owners, and IT leaders ask us most before an agent build. Still curious? Ask us on a discovery call.
How long until the first agent is live?
Days to weeks, never months or quarters. Many clients start with a 2-Day POC to see one working before committing to more.
Which AI models do you use?
We pick the right model for each job, from Claude and OpenAI to open-source options, and build so you can switch later without starting over.
What about wrong answers?
A chatbot pointed at your files will make mistakes. Production agents with validation, constrained outputs, and human checkpoints are built to catch them before they matter.
How do you keep our data private?
Agents run inside your environment, behind your access controls, on enterprise model settings that keep your data out of model training. Every action is recorded in an audit log.
How do you keep AI costs under control?
You see what every run costs from day one. We use the most cost-effective model that does the job well, and we only scale a workflow once it pays for itself.
Our data is a mess. Is that a problem?
Usually not. You do not need perfect data to get value from AI. We build with what you have, and tell you what to clean up and in what order.
Can our IT and security team review it?
Yes, and we encourage it. We build inside your access controls and walk your team through the safeguards, audit logs, and how data moves before anything goes live.
Who owns what you build?
You do. The code, the documentation, and the data stay with you whether we keep working together or not.
Tell Us the Work You Wish Ran Itself
Bring us the process your team dreads. We will show you what an agent could take off their plate, and how fast.
Book a Discovery Call- 01Discovery callWe walk through the workflow, the systems behind it, and what a win looks like for you.
- 02Prove it fastWe show it working on your real data, often in a 2-Day POC.
- 03Build and shipWeekly releases into production, with your team testing along the way.