Agents that do the work, not just chat.
We build AI systems wired into your actual tools and data: agents that run research, triage, and operations, and LLM features that live inside your product.
Every engagement starts with a scoping audit, credited toward the build. You get a fixed quote before any work ships.
Who it's for
Your team burns hours on work a well-built agent could run overnight.
You want AI in your product but not a thin wrapper around a chat box.
You tried no-code automation and hit its ceiling.
What we deliver
Custom AI Agents
Autonomous agents connected to your tools via MCP that run research, triage, and ops work with guardrails.
RAG Assistants
Support and sales assistants grounded in your own docs and data, deployed to web or app.
Workflow Automation
The manual steps between your tools, deleted. Triggered on schedules or events, observable end to end.
In-Product LLM Features
Generation, summarization, and classification built natively into your app with evaluation baked in.
Autonomous Content Engine
Automated research, drafting, optimization, and publishing that keeps your content fresh and on-brand.
How it runs
Map the work
We audit the workflow first: what's automatable, what needs a human gate, and what the failure modes are.
Build with guardrails
Agents get scoped permissions, human approval gates where it matters, and full audit logs.
Measure and expand
Every automation reports what it did. What works gets expanded, what doesn't gets fixed with data.
Frequently asked questions
Which models do you build on?
Model-agnostic by design, routed through a gateway so you can switch providers. We pick the model per task: quality, latency, and cost are all part of the choice.
How do you stop agents from doing something wrong?
Scoped permissions, approval gates for irreversible actions, and audit logs of every step. Autonomy is earned, not granted.
Is our data used to train models?
No. We build on APIs with zero-retention options and your data stays in your infrastructure wherever possible.
What does maintenance look like?
Models and APIs evolve fast. An optional care plan covers evaluation runs, prompt and model updates, and cost monitoring.
Let's scope your build.
Send us what you're making and where it's stuck. You'll get a straight answer on approach, timeline, and a fixed quote.