We build AI features that users pay for. Not demos. Not experiments. Production AI that increases revenue, reduces costs, and passes investor scrutiny.
You hire ML engineers. They build models. Six months later, you have impressive demos but nothing in production generating revenue.
Investors don't fund AI projects. They fund businesses that use AI to create value faster than competitors.
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
We work with 12 clients per year. Seven spots left for 2025.
Limited availability. Book your strategy session now.
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 strategy session. We'll review your AI use case, assess feasibility, and recommend approach.
No pressure. No sales pitch. Just honest assessment of whether AI makes sense for your business.
Book Strategy SessionIf we work together, the $5,000 applies to your project.