Consultants who
actually build
Strategic AI consulting from engineers shipping production systems daily. Not MBAs theorizing from slides.
Why we exist
They present. We build.
Traditional consultants sell 200-page PowerPoints. We ship working code. Our team: engineers who built 100+ production AI systems. We do not theorize—we have been shipping for a decade.
Execution over strategy
Strategy without execution is theater. We give you a roadmap, then build it. 95% of our clients reach production. Industry average: 13%.
Technical depth, not surface analysis
Our team writes production code daily. When we recommend GPT-4 vs Llama, it is from deploying both at scale. When we design architecture, it is from debugging at 3am.
Results, not reports
We measure success in production systems, not deliverables. Working prototype in week 1. Production by week 8. Our output: code repositories. Not PDF files.
The consulting industry has a production problem
| Firm | Avg Fee | Timeline | Prod Rate |
|---|---|---|---|
| McKinsey & Company | $5.2M | 16 months | 11% |
| Boston Consulting Group | $4.8M | 14 months | 15% |
| Deloitte Consulting | $3.9M | 18 months | 9% |
| Accenture | $4.2M | 20 months | 14% |
| TensorBlue | $500K | 8 weeks | 95% |
Traditional firms vs TensorBlue
"In 8 weeks, TensorBlue built what McKinsey spent 18 months planning. The difference is not competence—it is incentives. They sell time. We sell outcomes."— Chief Technology Officer, Fortune 500 Financial Services
We build real systems that generate real revenue
What we deliver
8 weeks from strategy to production
We have shipped with every major AI stack
Technology recommendations based on production experience, not vendor partnerships
AI strategy grounded in technical reality
Comprehensive audit of your organization to identify high-ROI AI opportunities. Not obvious applications—hidden automation wins that traditional consultants miss.
Having built 150+ systems, we know when to use OpenAI API vs fine-tune vs train from scratch. Vendor-agnostic recommendations based on actual TCO.
Should you hire ML engineers? Use agencies? Offshore? We have tried every model at scale. Recommendations based on your size and maturity.
Navigate GDPR, bias audits, model governance without paralyzing your team. Practical compliance strategies based on what actually gets through audits.
From concept to production revenue
Working prototype validates technical feasibility and business value
Production-grade system in staging with monitoring and CI/CD
Live system with load testing, security audit, team training
Continuous improvement based on production metrics
High-ROI use cases
Not every AI use case justifies investment. We identify the 20% of opportunities that drive 80% of value.
Deep domain knowledge across industries
Fraud detection, risk modeling, algorithmic trading
Diagnosis assistance, drug discovery, patient triage
Personalization, demand forecasting, search optimization
Quality control, predictive maintenance, supply chain
Who you actually work with
Design technical architecture. Choose models, infrastructure, deployment strategy.
Build, train, deploy AI systems. Write production-grade code that scales.
Guide AI adoption. Navigate organizational change. Measure and optimize ROI.
McKinsey vs TensorBlue
Results that matter
"TensorBlue built in 8 weeks what McKinsey spent 18 months planning."CTO, Fortune 500 Financial Services
How we replaced traditional consulting
McKinsey spent $5M, 18 months on fraud detection strategy. Zero code shipped.
We built production system in 10 weeks. 99.2% detection rate. $80M saved annually.
Gradient boosting + GPT-4 analysis layer
Traditional consultants proposed 24-month timeline for diagnosis assistant.
Medical LLM with RAG deployed in 8 weeks. FDA-compliant. 500+ doctors daily.
Fine-tuned Llama 3 + clinical guidelines RAG
Recommendation engine driving 5% revenue. Accenture wanted $3M to rebuild.
Hybrid recommender for $400K. Revenue from recommendations: 5% → 35%. ROI in 8 days.
Collaborative filtering + LLM embeddings
How we work together
Transparent investment structure
- — AI opportunity assessment
- — Technical architecture
- — Build vs buy analysis
- — Working POC
- — Implementation roadmap
- — 3-month advisory
- — Everything in Strategy
- — Full system development
- — Production deployment
- — Team training
- — Documentation
- — 6-month support
- — Multiple AI systems
- — Org-wide change
- — Dedicated team
- — Continuous optimization
- — Executive coaching
- — Unlimited support
What we guarantee
Prototype in Week 1. Not slides.
Full refund if we do not deploy.
10+ years experience minimum.
You own all IP. No vendor lock-in.
If your AI system does not reach production and generate measurable value, you receive a full refund. No consulting firm offers this. Because their success rate is 13%. Ours is 95%.
What executives say after switching
"McKinsey charged $5M for PowerPoints. TensorBlue charged $2M and delivered a production system generating $80M annually. Never working with traditional consultants again."
"Traditional firms spent 18 months planning. TensorBlue shipped in 8 weeks. The difference: they actually know how to build."
"Finally, consultants who execute. Our recommendation engine went from 5% to 35% of revenue in 2 months. $200M incremental annually."
Common questions
How are you different from McKinsey or BCG?
We build, they advise. Our team: senior ML engineers who write production code daily. Not MBA analysts who theorize from frameworks. 95% of our clients reach production vs 13% industry average.
What if we already hired a big consulting firm?
We have replaced McKinsey, BCG, and Deloitte at multiple Fortune 500 companies. Typically because they spent millions on strategy but could not execute. We review their recommendations and build the system—often for less than they charged for slides.
Do you work with our team or replace them?
We work alongside your engineers. Goal: upskill your team while we build together. By engagement end, your team can maintain and evolve the system independently. We build capability, not dependency.
How long to see results?
Week 1: working prototype. Week 4: MVP in staging. Week 8: production deployment. Traditional firms take 12-18 months for strategy alone. We ship production systems in the time they make slides.
What if the AI system fails?
Production-or-refund guarantee. If we do not deploy your system and generate measurable value, full refund. No traditional firm offers this. Their success rate: 13%. Ours: 95%.
How technical must we be?
You provide business context and data access. We handle all technical complexity. Translation of business problems into technical solutions: that is our expertise.
Post-launch support?
Every engagement includes 6 months: bug fixes, performance optimization, feature additions, team training. Unlike traditional consultants who disappear after the report, we stay until you succeed.
Ready to ship AI?
Not another strategy deck. A production system generating revenue.
Limited to 4 new clients per quarter