Technical assessment and part‑time CTO leadership for AI and complex software
I help investors and CEOs decide if a product, vendor, or acquisition is safe. Then I work with the team to fix the biggest risks and ship reliably.
Executive-ready assessment
Written decision • risk list • fix plan
Reliable AI
quality checks • safety rules • monitoring • cost limits
Delivery leadership
system design • reliability • release rhythm
Clean handover
playbooks • coaching • ownership transfer
Decision
"Is this vendor safe?"
"Is this acquisition hiding technical risk?"
"Is the AI claim real?"
Plan
Risks, options, and rough fix costs - in writing.
Execute
Reliability
Quality
Cost
I lead implementation with your team: releases, reliability, AI checks (if needed).
Executive-ready assessment
Written decision • risk list • fix plan
Reliable AI
quality checks • safety rules • monitoring • cost limits
Delivery leadership
system design • reliability • release rhythm
Clean handover
playbooks • coaching • ownership transfer
Services
Fixed-scope services
Clear scope, defined timeline, and decision-grade deliverables. No hourly billing.
Decision-Grade Technical Assessment
A technical due diligence and vendor assessment that turns ambiguity into an executive decision.
From €9k
- •Executive memo (go/no-go + key risks)
- •Risk register + remediation ranges
- •AI claims and unit economics sanity check
Fractional CTO / Principal Architect
Senior technical leadership to stabilize delivery, reduce risk, and make build-vs-buy decisions that stick.
From €6.5k/mo
- •Onboarding sprint: architecture + delivery diagnosis
- •Delivery operating system (quality, releases, metrics)
- •Vendor strategy, hiring bar, coaching
AI Operating Model Upgrade
Make AI usage consistent, safe, and measurable across real workflows, not random prompting.
From €5k
- •Role playbooks + quality criteria
- •Governance (data handling, tool approvals, evaluation)
- •Measurement plan (adoption, time saved, error reduction)
Final scope depends on access, integrations, and data readiness.
Prices exclude VAT.
Selected Work
Real systems, not demos
I focus on reliability, measurable outcomes, and clean handover.
Client names and sensitive details are omitted. The work and outcomes are real.
Mini case study
Turning supplier PDFs into usable CO2 data
Context: A team needed CO2 footprint data from many supplier documents to build an environmental tracking platform.
Risk removed: Manual extraction, inconsistent numbers, and unclear vendor responsibilities.
What changed: I assessed what can be automated, designed the extraction pipeline, wrote vendor specs, and defined clear boundaries between vendors (who delivers what).
Outcome: A vendor-ready plan with lower integration risk and controlled build cost.
Mini case study
Speeding up a long certification workflow
Context: A certification process took months and required repeated reading of requirements and gathering evidence across many documents.
Risk removed: Slow throughput, repeated work, and vague vendor deliverables.
What changed: We mapped the workflow, identified where AI can help safely, defined deliverables, and prepared a vendor spec (including inputs needed for funding).
Outcome: A clear execution plan designed to cut the time-to-complete dramatically (target: up to ~10x faster).
Mini case study
Getting an organisation ready to use AI safely
Context: An innovation centre wanted to apply AI, but legal questions and data-handling concerns blocked progress.
Risk removed: Stalled adoption and shadow AI use (people using unapproved tools with sensitive information).
What changed: I identified high-value use cases, listed the legal questions for their lawyers, clarified what data can be used where (based on their existing cloud setup), and helped the team build the first internal prototypes.
Outcome: A practical starting point: approved workflows, clear safe-use rules, and working prototypes built in-house.
Personal case study (engineering proof)
AI nutrition coach with live data integration
Built for my cycling training, then used as a repeatable pattern for production data integration, quality checks, and monitoring.
How should I fuel today? I have threshold intervals planned for tomorrow.
Checking your data from intervals.icu...
HRV
58 ↑12%
Form (TSB)
+7
TDEE
3,010
Today's targets (-500 deficit):
Higher carbs today, because your HRV is strong and tomorrow's threshold session needs glycogen.
The Challenge
I tracked training and wellness data but still struggled to turn it into practical daily nutrition decisions.
The Approach
I built an AI assistant that reads my training and wellness data from multiple apps, applies simple nutrition rules, and explains a daily plan so it is usable even when you are not an expert.
Results
Process
How I work
Diagnose
Interviews and artifact review produce an architecture map and risk register.
Decide
I document options, trade-offs, and a recommendation you can act on.
Execute & transfer
If needed, I embed as fractional CTO or principal architect and transfer ownership to your team.
About
20 years turning complex systems into predictable delivery
I've worked across telecom QoE research, UX, full-stack engineering, and applied AI. Today I help investors and product teams make better technical decisions and execute them without drama.
Decision-grade technical reviews
Due diligence, risk registers, and clear go/no-go advice
Architecture for delivery
Systems that optimize for shipping and operations
Evidence-first AI
Evaluation, guardrails, monitoring, and cost control
Coaching and handover
Playbooks and transfer so teams stay independent
Ing. Bruno Gardlo, PhD
Fractional CTO / Principal Architect (AI, architecture, delivery)
Need a clear yes/no on the tech - or CTO-level leadership to fix it?
Book a 30-minute call. If it's a fit, I'll recommend the right starting point.
I reply within 1 business day.