We come into your business, map your workflows, and find where AI is worth building. Then we build it with you. Real work, not slideware.
"They started with an audit of how we were doing things, sat down with our team, and came back with a clear report, workflow diagrams, and a plan for automating the whole thing."
Teams that get real results don't have an AI strategy. They have a business strategy and they know where AI accelerates it.
Every failed AI project skipped this step. You can't automate what you can't see. The mapping alone is usually worth the engagement.
Flashy demos get likes on LinkedIn. Eliminating 50% of the work nobody wants to do is what really changes a business.
Building is fast now. Knowing what to build requires sitting inside your business and watching how the work really gets done.
We've talked clients out of AI projects. If a process fix or a $40 SaaS tool solves the problem, we say so. Saves you money, keeps us honest.
You can redirect overnight. Less legacy, less coordination, easier to map. The work that used to require an enterprise IT team is now available to anyone willing to build.
Examples of the kind of AI systems we ship. Most engagements start with one and grow.
End-to-end billing engines that unify your data sources, apply your business rules, and eliminate manual export/import work. Backtested against real data before going live.
Full production builds. AI-powered web and mobile apps that we design, engineer, and ship. Web, iOS, Android, admin, and cloud infra all in one build.
AI capabilities embedded directly in your SaaS. Contract review, smart estimation, anomaly detection, automated decisioning. Native to your product, not an afterthought.
Purpose-built AI assistants trained on your proprietary knowledge, business logic, and internal expertise. Deep understanding of your domain, in your team's language, cited to source.
Autonomous AI agents that coordinate across your tools — CRM, ERP, docs, comms — to execute multi-step business processes end-to-end. Human in the loop on decisions that matter.
AI systems that make or support high-stakes business decisions — underwriting, pricing, risk scoring, prioritization. Your rules baked in, your data driving the model, fully auditable.
Three high-scope AI systems, before and after. Not utilities. Real engineering work that changes how a team operates.
Three ways to work with us. Start with one, grow into all three, or pick exactly what you need.
We come into your business, watch how the work actually gets done, and pinpoint where AI is worth building. The roadmap is yours, with or without us.
We design and build the AI work into your ops. Production-grade, integrated with your stack, owned by you when we're done.
We stay on as your AI operating partner. Monitor what's running, fix what breaks, build the next thing when you're ready.
Beyond the deliverables and the engineering, here's how the engagement actually runs.
Fixed scope, fixed quote, no surprise charges. You own everything we build. No lock-in, no required retainer.
We've talked clients out of AI projects more than once. If a process fix or a SaaS tool solves the problem, we say so.
The team you meet at kickoff is the team that delivers. No bait-and-switch, no offshore handoffs, no junior staff buried in our org chart.
Your people sit in the workflow reviews. Your engineers see how we score things. When we leave, your team can operate what we built.
Send a few details about your team and what you're trying to fix. A real person on our team will read it and reply within one business day, with a clear scope and quote if it's a fit.
Thirty seconds. No spam, no automated sequence.
Most engagements start with a Map (1-2 weeks). We come in, watch how your team works, audit your data, and surface 3-5 ranked AI opportunities. If we build it next (Build), it's typically a 4-12 week sprint to ship one workflow into production. Run is ongoing monthly support if you want us to stay on as an AI operating partner.
Production AI agents, RAG (retrieval-augmented generation) systems for internal knowledge, document parsing, workflow orchestration with AI decision steps, custom LLM apps, integrations between your tools, and the UI for your team to use any of it. We build with Claude, GPT, Gemini, and open-source models, picking what fits the job.
A Map runs $5,000 to $50,000 depending on org size and complexity (typically 2 to 6 weeks). Build projects are scoped individually, usually 4 to 12 weeks per workflow shipped. Run is retainer or time & materials, sized to what you're actually operating. Tell us what you're trying to do and we'll send a clear all-in quote within one business day.
Best fit: 50 to 500-person organizations with at least one process generating real data volume (support, sales, ops, contracts). We've also worked with smaller teams and larger enterprises, but the sweet spot is SMB / small enterprise where one engineer can make a real difference.
Always with. Your people sit in the workflow mapping, your engineers see how we build, your leaders shape what gets prioritized. We hand off cleanly with full documentation. If you want us to stay on through Run, we operate alongside your team, not over them.
We'll tell you. We've talked clients out of AI projects more than once. If a process fix, a hire, or a $40/month SaaS tool solves the problem, we say so. Saves you money. Keeps us honest. It's also why our Map phase exists, to figure that out before anyone commits to building.
Read-only access for the Map. For Build we'll need integration credentials but never destructive permissions in production. We work in staging until you sign off. Your environment stays in your team's hands.
It's a real concern. Models change, APIs deprecate, dependencies drift. Two answers: (1) we build with abstraction layers so swapping models or providers isn't a rewrite, and (2) Run exists for this reason. If you don't want a retainer, we hand off with playbooks and monitoring so your team can keep it healthy.
Tell us what's not working. We'll show you exactly where AI fits, what it would cost, and what to ship first.
