AI Integration
Add AI to your existing product — without breaking what works
Most AI integrations are bolted on and break in production. We design the feature properly, pick the right model, estimate operating costs upfront, and build it to survive real usage.
Fixed scope, fixed price. You see working software every week.
The problem with most AI features
Most AI integrations are prototypes that got promoted to production. They work in demos. They fail with real data, edge cases, and actual user behavior.
Common failure modes: API timeouts with no fallback. Malformed output crashing downstream code. No validation on AI responses before they hit your database. Zero cost controls — the feature works fine until you get 100x traffic and a $50,000 API bill.
We build production AI features. That means proper error handling, output validation, cost controls, fallback UX, and documentation your team can actually maintain.
Common AI features we build
These are the highest-value AI features for most products.
Document summarizer
Users upload contracts, reports, or PDFs. AI extracts key points, obligations, and action items. Works with 50-page documents.
Legal, finance, operations
Smart search
Search by meaning, not keywords. "Show me projects like the Henderson account" returns the right results without exact-match strings.
CRM, knowledge bases, product catalogs
Data extraction
Users paste unstructured text — emails, forms, receipts. AI returns clean structured data ready for your database.
Operations, finance, logistics
AI assistant / chatbot
Product-specific assistant grounded in your documentation, FAQs, or knowledge base. Actually answers questions, not just searches.
Customer support, internal tools, SaaS products
Classification and routing
Incoming support tickets, sales leads, or tasks automatically classified and routed to the right team or queue.
Support, sales ops, project management
Content generation
Draft generation from templates, data, or user inputs. Emails, reports, proposals — with your brand voice and review before sending.
Marketing, sales, client services
Every integration includes
Not just the happy path. Production-ready means handling failure, documenting everything, and leaving you with something your team can maintain.
- Feature scoping document with model recommendation
- Operating cost estimate before work begins
- Engineered system prompts with version control
- Output validation and error handling
- Fallback UX for API failures and timeouts
- Rate limiting and cost controls
- Monitoring and logging setup
- Inline code documentation
- Handoff notes for your team
Pricing
All prices are fixed-scope. Final price confirmed in written estimate after scoping call.
Common questions
Which AI model do you use?
It depends on the use case. GPT-4o, Claude 3.5 Sonnet, and Gemini Flash each have strengths. I recommend the right model for your feature and budget, and estimate operating costs before we start.
What does it cost to run AI features?
It varies widely. A document summarizer might cost $0.03 per request. At 100 uses/day, that's ~$90/month. I estimate this for you before we build, so you're not surprised post-launch.
Will you work with our existing codebase?
Yes. Most AI integration projects involve adding to an existing product. I'll review your stack and existing code before scoping.
What if the AI output is wrong?
AI is probabilistic. We design for this: output validation, confidence thresholds, human review flows, and clear UI that communicates when something is AI-generated vs. ground truth.
Do I need to fine-tune a model?
Almost never. Prompt engineering covers 90% of use cases. Fine-tuning requires thousands of labeled examples and rarely outperforms a well-engineered prompt. I'll tell you honestly when it's worth the investment.
Ready to add AI to your product?
Book a free scoping call. We'll discuss which AI feature would have the most impact, how to build it properly, and what it would cost.
Book a scoping call →