Architecture
Define or challenge the production system across models, data, services, security, integration, latency, scale, and operational boundaries.
Private production AI engagements
When the AI system has to work in production, put an experienced operator on the problem.
YakData works directly with sponsors and technical teams to get high-risk or blocked AI work to a defensible decision, production-ready design, working system, or clean handoff. When the problem requires it, the work extends through implementation and deployment.
Business consequence first.The technology matters because of the decision, workflow, risk, and operating result it must support.
Problems worth a private engagement
Use deeper ownership when the problem crosses system boundaries or carries material business consequence.
A private engagement is for work that cannot be resolved by generic advice, a vendor comparison, or another isolated prototype.
Production readiness
Determine what must be true before release, including failure behavior, monitoring, fallback paths, escalation, support, and ownership.
AI economics
Pressure-test model choice, operating cost, human review, throughput, engineering complexity, and whether the economics survive real usage.
Evaluation and verification
Build acceptance logic, benchmarks, failure tests, comparison baselines, and evidence strong enough to support a release decision.
Context and system definition
Resolve missing context, data semantics, retrieval, workflow boundaries, requirements, and the business decision the AI actually supports.
Consequential AI decisions
Support build, redesign, replace, narrow, deploy, expand, or stop decisions where technical uncertainty and business risk are intertwined.
Two engagement modes
YakData can own the decision, or drive the path through implementation.
The engagement should stop where the client's internal team can confidently take ownership. Delivery is available when the problem cannot be resolved without changing the production system itself.
Mode 01Advisory ownership
Get to the right decision and turn it into an executable path.
- Frame the consequential business and system decision
- Audit architecture, evidence, economics, controls, and assumptions
- Define requirements, acceptance logic, and production boundaries
- Compare credible alternatives and expose tradeoffs
- Produce decision records, architecture direction, and an executable path
Best when: your team can implement once the right decision and production path are clear.
Mode 02Delivery ownership
Build the production path when implementation is part of resolving the risk.
- Build the smallest production-shaped vertical slice
- Integrate data, AI, rules, backend, interface, testing, and human control
- Evaluate against explicit acceptance and failure criteria
- Deploy, instrument, monitor, and establish recovery behavior
- Transfer architecture, evidence, operating procedures, and ownership
Best when: the system itself must change before the decision can be considered resolved.
Production evidence
Optimize the system, not the prestige of the model.
65% lower model costwhile retaining approximately 98% of top-model performance in a production AI optimization.
That result did not come from asking which model was “best.” It came from defining the actual acceptance standard, testing alternatives, and optimizing against system economics.
What engagement ownership means
The work is organized around decisions, proof, and forward motion, not billable activity.
Define what must be true
Business consequence, sponsor, users, constraints, system boundaries, acceptance logic, and evidence required for the next decision.
Work the highest-risk uncertainty
Architecture, data, AI, UX, backend, testing, economics, and operations move concurrently in tight loops around the dominant risk.
Make the evidence visible
Tests, benchmarks, failure cases, architecture artifacts, system behavior, cost evidence, and decision records replace hand-waving.
Transfer ownership
The engagement ends with the client able to operate, challenge, change, monitor, and improve the system without dependence on YakData.
How private work starts
Start with the smallest engagement that can resolve the decision.
A $38K+ engagement should not be the default if a smaller intervention can establish the right answer.
1
Private Analysis Review · $2,500 when the system and decision need independent diagnosis before scope is clear.
2
Private Working Day · $7,500 when a concentrated problem can be resolved through deeper joint work.
3
Private Engagement · From $38,000 when the decision requires sustained advisory or delivery ownership.
Discuss your AI system
Describe where the system is stuck, what decision is open, and what happens if the team gets it wrong.
YakData will tell you the smallest sensible next step: a Private Review, a Working Day, a $38K+ engagement, or keeping the work entirely with your internal team.
Do not submit confidential data, credentials, proprietary source code, customer records, regulated data, or trade secrets.