We build, protect, and scale AI features that create real business value. so one bad technical call doesn’t cost you six figures and six months.
Whether your code was written by AI tools, offshore developers, a founding engineer who left, or your co-founder learning as they go. the problem is the same: you’re shipping fast, but nobody is asking whether you’re shipping right.
The mistakes that kill startups aren’t bugs. They’re decisions: the wrong architecture, the wrong database, the wrong framework, the shortcut that saves a week now and costs six months later.
That’s where we come in, not just to build, but to make sure what gets built can actually survive what comes next.
Three engagement lanes depending on where you are. all anchored in technical judgment.
Most teams build what you ask. We build what you actually need. and push back on the rest.
For founders who want a team that thinks like owners, not order-takers.
Your codebase is a liability you can’t see. We audit the decisions that will cost you later and give you a clear plan.
For teams shipping fast who need a second set of eyes before it’s too late.
You’ve got momentum. Now you need a technical partner who can grow with you and tell you what not to build.
For companies doing $500K-$5M+ in revenue who want ongoing leadership without a full-time CTO.
AI isn't just training a model. It's infrastructure, monitoring, updates, and business integration.
We build the second one.
Not everything needs AI. We only build AI when it creates clear business value.
Extract data from PDFs, invoices, receipts. Parse unstructured documents. OCR with validation.
Business value: Reduce manual data entry by 80%. Process documents 10x faster.
AI chatbots that actually help. Ticket classification and routing. Suggested responses for agents.
Business value: Reduce support costs 40-60%. Faster response times.
Product descriptions at scale. Email personalization. Marketing copy variations.
Business value: 10x content output. Reduce writing time 70%.
Product recommendations. Content suggestions. Personalized feeds. Similar item matching.
Business value: 20-30% increase in engagement. Higher conversion rates.
Semantic search. Natural language queries. Vector similarity search. Hybrid search systems.
Business value: Users find what they need 3x faster. Reduced bounce rates.
Churn prediction. Lead scoring. Demand forecasting. Anomaly detection.
Business value: Proactive interventions. Better resource allocation.
Before we build anything, we validate that AI will create value.
Example: "Reduce invoice processing time from 10 minutes to 30 seconds, saving $200K/year"
AI quality depends on data quality. We audit what you have: availability, quality, and requirements.
We're honest about data requirements. Bad data = failed AI project.
We build minimal AI that proves value before investing in scale. Model selection, training, integration, and testing.
Working AI feature in 4-6 weeks with real accuracy metrics and cost projections.
Infrastructure, monitoring, and safety rails. API layer, model serving, monitoring, input/output validation, rate limiting.
Most startups should start with LLM APIs, not custom models.
RAG lets LLMs answer questions using your company's data without retraining.
Timeline: 4-6 weeks | Investment: $60K-$100K
AI can get expensive at scale. We optimize for cost from day one.
We've reduced AI costs 70% through optimization while maintaining quality.
A fintech startup manually processed 10K invoices monthly. Each invoice took 8 minutes. Total cost: $150K/year in labor plus errors and delays.
Week 1-2: Analyzed invoice formats, assessed data quality, calculated ROI
Week 3-6: Built classifier, trained extraction model, integrated with workflow
Week 7-8: Deployed to production, set up monitoring, trained team
Processing time:
8 min → 45 sec
Labor cost:
-70%
Error rate:
5% → 0.8%
Processing capacity:
10K → 50K/month
Business case validation, data preparation, model development, production deployment.
Investment: $80K-$150K
RAG system setup, vector database, monitoring and logging, safety rails.
Investment: $100K-$180K
Data collection and labeling, model architecture design, training and optimization, production deployment.
Investment: $150K-$250K
Use case identification, data assessment, technical feasibility, cost-benefit analysis.
Investment: $30K-$50K
If you nodded at even one of these. let’s talk. The first call is free and there’s no pitch.
Free 15-minute strategy call. No pitch, just clarity.
Most dev shops are order-takers. We review the plan, challenge assumptions, and build with the full picture in mind. You’re not paying for code. You’re paying for judgment that saves expensive mistakes.
That’s fine. We do plenty of straight development work. with one difference: we’ll still flag risks and push back on bad decisions. That’s not an upsell. It’s how we work.
Yes. Start with a free 15-minute strategy call, then choose the lightest engagement that makes sense. Most clients start small and expand once we prove value.
Simple feature: 6-10 weeks. Complex system: 12-16 weeks. Custom models: 16-20 weeks.
Feature: $80K-$150K. Infrastructure: $100K-$180K. Custom models: $150K-$250K.
Start with OpenAI/Anthropic. Build custom only when volume justifies it (usually 1M+ requests/month).
Typically 6-12 months. Depends on cost savings or revenue generated vs development cost.
We optimize from day one. Caching, prompt optimization, model selection reduce costs 50-70%.
Book a free 15-minute strategy call. We'll review your AI use case, assess feasibility, and outline the fastest path to production value.
No pressure. No sales pitch. Just honest assessment of whether AI makes sense for your business.
Book Free 15-Min Strategy CallIf we decide to do a Technical Health Check ($7,500), that fee is credited toward your first month.