AI & Machine Learning

AI-Powered Applications

We build AI features that actually work in production: chatbots, automation, and intelligent workflows using Claude, GPT, and open-source models

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1What We Actually Build

We integrate large language models into real business applications. That means chatbots that handle customer questions using your actual documentation, document processing that extracts structured data from invoices and contracts, and workflow automation that replaces manual steps with AI-driven decisions. We've built these with Claude, GPT-4, Gemini, and self-hosted Llama models. The right choice depends on your budget, privacy requirements, and use case.

2How We Work with AI

We use RAG (Retrieval-Augmented Generation) for chatbots that need to answer from your own data. We use LangChain and custom pipelines for multi-step workflows. We use function calling and tool use for AI agents that interact with your existing APIs. We don't just call an API and hope for the best. We build evaluation pipelines, handle edge cases, and test outputs against real scenarios before going live.

3Projects We've Shipped

ProductAI: an AI scrum master that turns product roadmaps into auto-scheduled backlogs using RAG-based code intelligence and GitHub velocity tracking. SimplyRecruit.ai: an AI recruitment platform that processes CVs and generates structured candidate notes automatically. Both are in production, handling real users and real data daily. Read more about how we use AI tools in our development workflow in our guide to AI-assisted development.

4Our Process

We start with a prototype sprint to test the AI functionality on your actual data. This takes 1-2 weeks and gives you something real to evaluate, not a slide deck. If it works, we build the production version with proper error handling, rate limiting, cost monitoring, and fallback logic. If the AI approach doesn't work for your use case, you find out in two weeks instead of four months.

5Data Privacy

AI applications often handle sensitive data. We offer on-premise deployment with self-hosted models when data can't leave your infrastructure. For cloud deployments, we use API providers with zero-retention policies and implement encryption in transit and at rest. All solutions comply with GDPR.

Let's build something

Bring your idea. Leave with a clickable prototype.

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