Product Strategy and Discovery
Problem, users, scope and success measures worked out before the build, so the first release does the right job.
Decisions Before Code
Advice from people who build: what to build, how to architect it, where AI genuinely fits and whether to build or buy, before you commit the budget.

Problem, users, scope and success measures worked out before the build, so the first release does the right job.
An independent review of structure, security, performance and delivery practices, with every finding rated by risk and effort.
Use cases ranked by value, data and risk, with a pilot plan and the controls needed to run AI safely in production.
How it fits together
We assess where you are, set out the options, then sequence the work into now, next and later, with a review gate before each step.
Assess
| Now | Next | Later | |
|---|---|---|---|
| Product | |||
| Architecture and code | |||
| AI and data | |||
| Team and vendors |
Review gate
Now
Review gate
Next
Review gate
Later
01Phase 1
We interview the people involved and assess the product, code, data and team as they are today, with read-only access wherever possible.
02Phase 2
Each option is set out with its cost, risk and trade-offs, then sequenced into a roadmap and business case you can fund.
03Phase 3
Leadership reviews the plan with us. Your team, another vendor or ours can then deliver it, with the written plan in hand.
How we work
Recommendations come from engineers who ship production systems and know what each option costs to run.
Every engagement ends in a document your team, board or another vendor can act on.
Build versus buy is answered honestly, even when the answer is not us.
Assessments run under a confidentiality agreement, with read-only access wherever possible.

Assessment
A fixed-scope audit of product, code, data or AI readiness.
Roadmap
Discovery and planning that ends in a sequenced, budgeted plan.
Fractional CTO
Ongoing technical leadership for an agreed number of days each month.
Founder contribution delivered as part of professional work at BlandLabs.
Read the case studyFounder contribution: part of the team that migrated and redesigned the U2D (User to Dealer) application for Skoda Auto Deutschland.
Read the case studyFounder contribution delivered during prior professional engagements.
Read the case studyEngineers who build. Our founder brings 9+ years of building production systems across voice AI, computer vision, web and mobile, and every recommendation is reviewed by people who could build it themselves.
Part-time technical leadership for a company that needs senior judgement but not a full-time executive: architecture decisions, hiring and vendor oversight, roadmap ownership and a technical voice in leadership meetings, for an agreed number of days each month.
No. Build versus buy is an honest question: if an existing product or another vendor fits better, the recommendation says so. If you then want us to build, that is a separate engagement.
We look at the workflows worth automating, the data they depend on, the risk if an answer is wrong and the team that will own the system. The result is a ranked list of use cases with a pilot plan, not a general AI strategy.
A written report on structure, security, performance, test coverage, dependencies and delivery practices, with each finding rated by risk and effort and a sequenced plan to fix what matters first.
Yes. Assessments run under a confidentiality agreement, access is read-only wherever possible, and your confidential information is never reused for another client's work.
Clear confidentiality and IP terms. Your confidential information is never reused for another client's work.
Book a free 30-minute consultation, or write to us, you will always talk directly to the person who builds your product.
Techon Pixel · info@techonpixel.com