Custom AI Agents
Task-specific agents prompted, tuned, or fine-tuned to handle real workflows: research, drafting, intake, classification, routing, monitoring.
Services / Applied AI
AI that does real work.
Most AI projects stop at a chatbot. We build the agents, automation pipelines, and AI-augmented tooling that handle real operational work, like research, intake, routing, drafting, and monitoring, inside the systems your team already uses.
What we ship
Automation Pipelines
End-to-end automations that connect your tools: CRM, email, calendar, fulfillment, billing. AI in the loop where it matters; deterministic where it doesn't.
AI-Augmented Internal Tools
Dashboards, admin panels, and operator interfaces with AI built in. Your team operates at higher leverage without learning new platforms.
Voice & Conversational Systems
Voice agents, transcription pipelines, conversational interfaces. Built on production-grade models with real latency and cost engineering.
Model Selection & Cost Engineering
Right model for the job. We benchmark across providers (Anthropic, OpenAI, open-source) and tune for accuracy, latency, and cost.
Integration with Existing Systems
AI that lives where your work lives. Native integrations with the platforms you already pay for, no rip-and-replace.
How we work
Workflow first, model second
We start with the bottleneck, not the model. Show us where time leaks and we design the smallest AI system that solves it.
Ship in weeks, not quarters
Most Applied AI engagements ship a working v1 within 2 to 6 weeks. Iterate from there with real usage data.
You own the code
We hand off clean, documented code into your repos and your infrastructure. No agency lock-in, no opaque platforms.
Who this is for
- Operators with workflows that should already be automated
- Teams paying for software they don't fully use because integration is missing
- Founders building AI-native products who need real engineering, not prompt hacking
- Established businesses adding AI to existing platforms and operations
Frequently asked questions
What does an Applied AI engagement actually look like?
Typically: a 30-minute scoping call, a written proposal with scope and price, then a 2 to 6 week build. We work in your stack, hand off clean code or operational documentation, and stay available for changes.
Which AI provider do you use?
Depends on the job. We benchmark across the major commercial and open-source model providers and pick the model that fits your accuracy, latency, and cost needs. We're not loyal to any one vendor.
Do you handle deployment, or just write the code?
Both. We can deploy to your infrastructure or set up new infrastructure using managed hosting and database services. You own the code and the keys either way.
How do you handle data privacy and security?
We work with whatever data boundaries you need. On-premise deployment, VPC-only setups, or zero-data-retention model providers when sensitivity is high. We sign NDAs and DPAs before sensitive data touches our systems.
What's the cost of a typical project?
Pricing depends on scope. We quote each project after a scoping conversation. See our pricing page for how we approach it.
Will the AI actually work, or is this hype?
We won't take a project we don't think will deliver. Part of our scoping process is being honest about whether AI is the right tool. Sometimes the answer is a simple rule-based automation. We'd rather lose the engagement than ship something that doesn't perform.
Have something to build?
Tell us what you're working on. We'll come back with how we'd approach it, including whether we're the right fit.
Get in touch →