Understand the business.
We begin with the result you want, not a predetermined technology. A focused, fixed-price discovery starts around $15k and examines the work, people, data, systems, and constraints behind the opportunity.
Applied AI consulting · Discovery + delivery
What could your business do with AI?
You see the potential. What you may not see yet is the right place to begin. Akayima works with business leaders and their teams to find where AI could make a meaningful difference, identify the strongest opportunity, and turn it into a practical project with a clear path to implementation.
Akayima takes its name from the northern green anaconda, a constrictor. Like Eunectes akayima, we get a grip on the problem, then make the solution tighter until the job is done.
How we work
Find the work worth changing. And the project worth funding.
You do not need to arrive with the use case. Discovery turns a broad mandate, a dozen ideas, or a stubborn business problem into a confident decision about what to pursue first—and what not to pursue yet.
Choose the opportunity.
Possible use cases are judged on business impact, feasibility, risk, adoption, cost, and time to value. You leave with a recommended first project, success criteria, solution approach, roadmap, milestones, and price.
Build what matters.
When there is a strong case to proceed, Akayima can carry the project through architecture, implementation, evaluation, deployment, and handoff. Implementation is fixed-price and milestone-based, with working progress shown along the way.
Projects + results
Experience turning complicated work into measurable improvement.
Over eight years, Adam has built AI, data, and operational software across education, financial services, and e-commerce. This is the experience behind every Akayima engagement.
8years building AI, data, and operational software
~30clients served through independent consulting
80–90%estimated expert-review reduction on one medical-content workflow
~5%gross-margin improvement from one pricing-workflow rebuild
A more efficient path through expert review.
A metadata platform mapped medical learning content to canonical objectives and routed the results through expert review—reducing estimated reviewer effort by 80–90% while preserving expert sign-off where it mattered.
A shared approach to AI evaluation.
An evaluation framework aligned AI-generated learning content with human judgment across summaries, quizzes, scoring, and feedback. The approach is being extended across 10–20 enterprise AI products.
Knowledge tools for operational teams.
An internal knowledge and retrieval system supported several hundred employees across lending, underwriting, engineering, HR, and related operations.
Better economics through better operational software.
A rebuild of pricing, validation, and correction workflows across tens of thousands of products improved overall gross margin by roughly 5% and eliminated a recurring class of negative-margin products.
Our philosophy
The goal isn't more AI. It's better work.
Start with the business outcome, keep people in control where judgment matters, and measure the finished system by how well it works in practice. AI has to earn its place.
About Akayima
Senior expertise, directly involved from discovery through delivery.
Akayima is led by me—Adam Roach. I work directly with client leaders and the people closest to the work, then carry the engagement from an open business question through technical discovery and, when it makes sense, into a dependable production system.
Over eight years, I've shipped AI and data systems in medical education, financial services, e-commerce, and marketplace operations. By day I build production RAG pipelines, evaluation frameworks, and agentic systems for a major education publisher. My experience spans the full path from business requirements and solution design through data, application development, AI evaluation, deployment, and handoff.
That means the person helping you decide what to build is also someone who understands what it takes to build it well.
A few receipts
- Production AICore engineer on an LLM voice simulation product live at 15+ institutions and used by thousands of students — from data and prompts through scoring, feedback, red-teaming, and guardrails.
- Evaluation & efficiencyBuilt an evaluation framework being extended across 10–20 enterprise AI products, and cut one production scoring loop’s LLM cost by roughly 95% through model, call, and token optimization.
- Commercial ownershipRan an independent practice serving roughly 30 clients. Rebuilt pricing across tens of thousands of SKUs, lifting gross margin by about 5% while taking recurring catalog errors from roughly 15% to zero.
- Technical foundationEight years across applied AI, forecasting, data products, and full-stack delivery — backed by an M.S. in Statistics from Georgia Tech and a B.S. in Mathematics from UT Austin.
Based in Dallas, Texas. Working with teams anywhere.
Good to know
Questions you might have.
- Do we need to have an AI use case in mind?
- No. A broad goal, business problem, or area of opportunity is enough. Discovery is designed to identify and evaluate possible use cases before you commit to building one.
- What size organization is a good fit?
- Akayima works well with small and midsize businesses, as well as business units or functional teams inside larger organizations. The important factor is having a meaningful problem, access to the people and systems involved, and an owner who can act on the outcome.
- What does discovery produce?
- You receive prioritized opportunities, a recommended first project, a workflow and systems assessment, feasibility and risk findings, success criteria, a proposed solution, and an implementation roadmap. When Akayima is the right delivery partner, discovery also ends with defined implementation scope, milestones, and a fixed price.
- How much does discovery cost?
- Discovery engagements start around $15,000. The exact scope and price depend on the breadth of the business area, the number of stakeholders and systems involved, and the uncertainties the engagement needs to resolve.
- What if AI is not the right answer?
- Then the recommendation will say so. Discovery may point to conventional software, a process change, a narrower role for AI, or a decision not to build. The goal is a better business outcome, not an AI project at any cost.
- Can Akayima build the solution after discovery?
- Yes. When the opportunity is strong and the fit is right, Akayima can lead implementation through architecture, development, evaluation, deployment, and handoff. Implementation is fixed-price and organized around defined outcomes and milestones.
- Who owns the finished work?
- Bespoke client work is delivered to the client. Akayima retains its existing tools, methods, and reusable components; anything incorporated into the solution is licensed for the client’s continued use. The exact terms are documented before work begins.
- What happens after launch?
- Projects include a defined stabilization period, documentation, and a practical handoff. Akayima can also remain involved through optional AI engineering and advisory support, or scope additional capabilities as new projects.