AI-Accelerated Development
Our engineers decide how your system should be built, then use GitHub Copilot, Claude, and Cursor to read legacy code faster and prototype features in hours instead of days. Think of us as the general contractor running a team of AI subcontractors. AI can frame a wall fast, but it doesn't know whether the foundation will hold in your soil. A senior engineer with decades of experience owns the code and reviews every line before it reaches production.
Find the AI Worth Building
Most AI features stall after the demo, when the answers are wrong too often or the data isn't ready. We start with a Discovery Workshop that looks at where your people lose time and where your data already holds answers, then rank the ideas by what they would return. You leave with a plan, an estimate, and a recommended architecture.
If the discovery doesn't provide value, you don't have to pay for it.
AI Smart Features We Build
Chatbots & AI Assistants
We build conversational AI and chatbots that answer from your own product catalogs, account history, and policy documents, for customer support or for staff working through complex workflows.
AI Search
We use semantic search and retrieval-augmented generation (RAG) so people can ask questions of your contracts, manuals, policies, and database records. The same tools can flag clauses that conflict across documents.
Predictive Machine Learning
Machine learning models trained on your own history can forecast demand, detect fraud, predict which customers are about to leave, or optimize inventory.
Text Analysis
Support tickets, emails, and reviews pile up faster than anyone can read them. Natural language processing sorts, tags, summarizes, and gauges sentiment automatically, so you see what's changing without reading every message.
Computer Vision
Computer vision can check what people now check by hand: damage, safety equipment, product quality, or shipment condition. Your team reviews the exceptions instead of every photo.
AI Agents
AI agents can handle routine steps in a workflow, like filling in forms or suggesting the next action, with a person approving the decisions that matter.
Who Does the Work
A senior engineer leads the work from architecture through delivery, so the people who designed your system are the ones building it. You decide what data the AI can see and where the model runs: a cloud service, a private deployment in your own cloud account, or your own servers. We choose models and set usage limits with you so your monthly AI costs stay predictable. You own all of the code and documentation.
You'll see working software at the end of every sprint, including how the AI behaves on your real data, so you can change course early.
What Happens After Launch
AI features need care after they ship: models change, data drifts, and new uses come up. We can stay on to monitor and improve them, or hand them to your team.
Tell us about the AI feature you're weighing or the software you want built faster, and we'll talk it through with you on a call.
