AI Integration
Turn your product into an
AI-native experience.
Integrate LLMs, RAG systems, and intelligent agents into your existing stack. We build production-ready AI features that solve real problems—not demos that break in production.
When AI Makes Sense
When AI integration
makes sense.
Not every problem needs AI, but when it does, the impact is transformative. Here's when AI integration delivers real value.
Support Volume is Exploding
Your team is drowning in repetitive questions and manual workflows. AI can automate responses and route complex issues intelligently.
Copy-Paste Between Tools
Your team spends hours moving data between systems. AI agents can automate these workflows and eliminate manual errors.
Users Want Smarter Features
Your product feels static while competitors add AI-powered experiences. You need intelligent features that actually work.
AI Prototype Isn't Production-Ready
You've built a proof-of-concept, but it's unreliable, expensive, or breaks under real usage. You need production-grade AI.
Solutions
What we actually build
Concrete AI integrations that solve real problems. Each one ships with production-grade reliability, monitoring, and cost optimization.
LLM Copilots & Chat Interfaces
Intelligent assistants embedded directly in your product—helping users navigate, answer questions, and complete tasks.
- Reduced support tickets by 40-60%
- Faster user onboarding and feature discovery
RAG Search Over Your Data
Semantic search that understands context, not just keywords. Users find exactly what they need from your docs, knowledge base, or internal data.
- 90%+ accuracy vs. traditional search
- Instant answers from complex documentation
AI-Powered Workflows & Agents
Autonomous agents that handle multi-step processes—from data processing to customer onboarding to internal automation.
- Eliminated 10+ hours/week of manual work
- Zero-error automation for repetitive tasks
Voice & Multi-Modal Interfaces
Voice recognition, image analysis, and conversational interfaces that make your product accessible and intuitive.
- Improved accessibility and user engagement
- Support for hands-free workflows
Intelligent Content Generation
AI that generates, summarizes, and personalizes content at scale—from product descriptions to reports to user communications.
- 10x faster content creation
- Personalized experiences at scale
Predictive Analytics & Insights
AI models that surface patterns, predict outcomes, and recommend actions based on your business data.
- Data-driven decision making
- Proactive issue detection
Process
How AI integration projects run
A streamlined process designed for speed and validation. We ship prototypes fast, validate with real users, then productionize what works.
View full processDiscovery & Feasibility
We identify high-ROI use cases, audit your data sources, and validate technical feasibility. You get a clear roadmap and ROI estimate.
Prototype & Validate
We ship a working prototype of your highest-value AI feature. You test with real users and validate the approach before committing to full build.
Productionize & Optimize
We harden the system for production—adding monitoring, cost optimization, safety guardrails, and performance tuning. Your AI feature goes live.
Iterate & Scale
We monitor performance, optimize costs, and iterate based on real usage. As your needs grow, we scale the solution and add new capabilities.
Work
AI-powered products we've built
WhatDo
AI travel planner helping you navigate destinations, generate day plans, and discover local experiences.
FoxyAI
AI content studio that grows your audience and builds your brand with intelligent automation.
Crolens
AI-powered Croatian news aggregator that curates and processes content from multiple sources using AI.
Nory
AI-powered restaurant management platform helping restaurants optimize operations, reduce costs, and improve customer experience.
Technical
Production-ready AI stack
We use battle-tested tools and patterns to ensure your AI features are reliable, cost-effective, and scalable. No experimental frameworks—just proven technology that works in production.
Read our AI engineering blog postsLLM Providers
RAG Stack
Vector databases (Pinecone, Weaviate, Supabase), semantic search, caching layers (Redis), and observability tools for monitoring cost and latency.
Integration
Seamless integration with Next.js, React Server Components, and your existing backend. Type-safe APIs, streaming responses, and production-ready error handling.
Production Features
- Cost monitoring & optimization
- Latency tracking & alerts
- Safety guardrails & content filtering
- Fallback strategies for model failures
Engagement
Engagement models & pricing
Choose the model that fits your needs. From quick discovery sprints to full integration builds to ongoing optimization—we adapt to your timeline and goals.
AI Discovery Sprint
Fixed-price sprint to identify AI opportunities, validate feasibility, and create an implementation roadmap.
Features
- AI opportunity audit
- Technical feasibility assessment
- ROI analysis & prioritization
- Implementation roadmap
Ideal for
- Teams exploring AI for the first time
- Companies with unclear AI use cases
- Organizations needing ROI validation
AI Integration Build
Fixed-scope development of a specific AI feature, from prototype to production-ready deployment.
Features
- End-to-end AI feature development
- Production-ready deployment
- Monitoring & observability setup
- Documentation & handoff
Ideal for
- Teams with validated AI use cases
- Companies ready to build specific features
- Organizations needing production-grade AI
Ongoing AI Optimization
Retainer-based support for monitoring, optimizing, and iterating on existing AI features.
Features
- Performance monitoring & alerts
- Cost optimization
- Model updates & improvements
- New feature experiments
Ideal for
- Teams with AI features in production
- Companies needing ongoing optimization
- Organizations scaling AI capabilities
FAQ
Common questions about AI integration
How do you handle data privacy and security?
We follow security best practices: data encryption in transit and at rest, no training on your data unless explicitly requested, and compliance with GDPR, SOC 2, and other relevant standards. We can deploy AI features entirely within your infrastructure if required.
Where is our data stored and processed?
We work with you to determine the best approach. Options include processing entirely on your servers, using your cloud infrastructure, or leveraging secure third-party APIs (OpenAI, Anthropic) with data residency controls. We never store your data longer than necessary for the feature to function.
How do you evaluate if AI is feasible for our use case?
During our Discovery Sprint, we assess your data quality, technical constraints, and business requirements. We build small prototypes to validate assumptions before committing to full development. If AI isn't the right fit, we'll tell you upfront.
What happens if we don't have clean, structured data?
We can work with unstructured data—documents, PDFs, text files, and even raw text from your product. We'll help you identify what data is needed, clean it if necessary, and build ingestion pipelines. Often, we can start with what you have and improve data quality over time.
How do you handle model changes or vendor lock-in?
We design AI integrations with abstraction layers, so you can switch models or providers without rewriting your entire system. We also implement fallback strategies and monitor model performance, so you're notified if quality degrades or costs spike.
What's the typical ROI for AI integration projects?
ROI varies by use case, but common outcomes include: 40-60% reduction in support tickets, 10+ hours/week saved on manual tasks, and improved user satisfaction scores. During Discovery, we'll provide specific ROI estimates based on your metrics and goals.
Ready to integrate AI into your product?
Book a free 30-minute discovery call. We'll discuss your use case, evaluate feasibility, and outline next steps.