Most AI fails inside companies for predictable reasons.
Public models are broad, generic, and detached from the actual rules that govern a business. They can sound plausible while missing policy nuance, brand tone, operational constraints, and exception handling.
Namakan exists to close that gap. We build AI around private business context so the system can do work in a way that is grounded, controlled, and genuinely useful to the team.
Close to operations
We spend time with the documents, decisions, exceptions, and real edge cases that shape day-to-day work.
Evaluation before polish
We test whether the system behaves correctly before we worry about slick demos or generic interfaces.
Systems over slogans
The goal is not to sound intelligent. The goal is to complete work with the right context and control.
Mid-market businesses with proprietary data they need to leverage.
Companies with 5–500 employees who have accumulated years of domain-specific knowledge — service records, contracts, case histories, SOPs, field notes — that lives in documents, CRMs, and databases but is not accessible to their tools or people in a useful way.
We typically work with operations, legal, compliance, and service teams. Engagements start at $5K and go up to $40K for broader rollouts. Most clients come through referrals from satisfied customers and professional networks in the Minneapolis–St. Paul area and beyond.
Clint Follette — Founder
Custom AI engineering with a focus on fine-tuning, agentic workflows, and systems that actually complete work. Based in Blaine, MN.
Namakan operates as a small, focused team — built for depth on each engagement rather than volume. When a project needs additional capacity, we bring in trusted collaborators from our network.
Email hello@namakanai.com to start a conversation. Include a description of the workflow, team, and business problem you are trying to solve — the more context, the better.
We respond within 1 business day. For teams exploring a project, we often start with an AI Assessment ($2,500, credited toward any subsequent engagement) to evaluate fit and map the opportunity before committing to a full build.