Add AI to the Software You Already Ship. Do It Right.
Clean, observable LLM integration for SaaS products: support automation, in-product assistants, intelligent search, content generation. Your users get AI that works. Your team gets a system they can maintain. Built with the FDE framework.
LLM Integration Is Easy to Start and Hard to Do Well
First prototype takes a weekend. Production system takes a team and answers to questions most skip: What happens on unexpected output? How to trace a bad output? Who owns the prompt?
SaaS teams that ship fast without observability end up with AI features that work until they don't.
HOW WE DO IT
Integration That's Observable, Maintainable, and Built to Last
Clean Integration Architecture
Encapsulated, upgradeable. AI layer separated from your app so model swaps, prompt changes, and version upgrades don't cascade through your codebase.
Prompt Management
Versioned, testable, separated from application code. Prompts treated as first-class artifacts with rollback, A/B testing, and clear ownership.
Observability from Day One
Latency, token usage, quality metrics, cost tracking. You see what the AI is doing, how fast, and how much it costs before your users complain.
Fallback & Degradation Logic
When the model is slow, down, or returning garbage, your product still works. Graceful degradation that protects UX and user trust.
Output Validation
Structured outputs, confidence scoring, guardrails. Every response checked before it reaches the user. No hallucinations leaking into production.
Multi-Model Flexibility
Not locked to one provider. Architecture designed to swap models, route by task, and take advantage of new releases without re-engineering.
In-Product AI Surfaces
Assistants, search, suggestions designed as native product features, not bolted-on chatbots. Contextual, useful, and aligned with your UX.
WHERE IT PAYS OFF
AI Features That Change Products
Support Automation
Intelligent triage, suggested replies, automated resolution for common queries. Support team handles the hard problems; AI handles the rest.
In-Product Assistants
Contextual help, onboarding guidance, and proactive suggestions based on what users are doing right now (not generic docs links).
Intelligent Search
Semantic search across product content. Users describe what they need in natural language and get relevant results, not keyword matches.
Content Generation
Drafts, summaries, structured outputs. AI that writes in your product's voice with guardrails that keep quality consistent.
Cross-Sell Intelligence
Contextual nudges from usage patterns. Recommendations that make sense because they're grounded in what the customer is actually doing.
IN PRODUCTION
In Production: TOSM
5 interconnected products. Over 5 two-week sprints (10 weeks): unified dashboard, AI-powered BI, contextual cross-sell nudges. Designed to be maintainable post-handoff.
to existing customers
Designed to be maintainable post-handoff. Clean integration architecture means the internal team owns it from day one of production.
What AI Feature Would Change Your Product?
You bring the product and the use case. We'll design the integration, define the architecture, and ship it cleanly, observably, in a timeline your roadmap can absorb.
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