AI that works inside your product.
Assistants, agents, search and automation from one team: a working pilot in 2–4 weeks, then production.
Six ways we put AI to work.
- Explore AI integration →
AI Integration
Plug assistants, smart search, document processing and predictive insights into the app you already have, without a rebuild.
- Chatbots
- Semantic search
- Predictions
- Explore AI agents →
AI Agent Development
Agents that plan, use your tools and finish multi-step work in sales, support and operations, with a human approving what matters.
- Multi-agent
- Tool use
- Human in the loop
- Explore generative AI →
Generative AI Development
Text, image and personalization features that are on-brand, moderated and cost-controlled, from first prototype to millions of generations.
- Content
- Images
- Personalization
- Explore LLM & RAG →
LLM & RAG Development
LLM apps that search your documents, data and tools and answer with sources, so your team and customers can trust every reply.
- Knowledge base
- Document Q&A
- Private LLMs
- Explore AI MVP →
AI MVP Development
From idea to a live AI app on iOS, Android or web, validated with real users, ready for investors and built to scale.
- Discovery
- UX/UI
- Launch
- Explore automation →
AI Process Automation
AI takes over invoices, emails, data entry and reports, so your team spends its hours on decisions, not paperwork.
- Documents
- Email triage
- Reports
Not sure which one you need?
- Add AI to the product you haveStart with one feature your users ask for: search, an assistant or document handling. Pilot in 2–4 weeks.AI integration →
- Turn your documents into answersDocs, tickets and databases become an assistant that answers with sources and respects access rules.LLM & RAG →
- Launch a new AI product in 8 weeksWe scope, design and build the first version with you, then keep it growing after launch.AI MVP →
From idea to AI in production.
- 01day 1
Free call
Your goals, data and users. We tell you honestly whether AI is the right tool.
- 021–2 weeks
Audit & data check
A quick test on your data, a costed plan and the model choice.
- 032–4 weeks
Pilot
A working feature in front of real users, with measurable results.
- 04ongoing
Production
Monitoring, evals and cost control as usage grows.
AI we have already shipped.
Travel · iOSJRNEY AI
An AI travel planner that builds day-by-day trips from a short chat with the traveler.
View full case →
Productivity · macOSRecordr
A meeting recorder with AI transcripts, summaries and action items — ready the moment a call ends.
View full case →
Healthcare · Web & mobileTelemedicine
A care platform with AI-driven health monitoring and personalized treatment plans.
View full case →
The AI tools we build with.
LLMs & models
- OpenAI
- Claude
- Gemini
- Llama
- Mistral
- Hugging Face
Frameworks & runtimes
- LangChain
- LangGraph
- LlamaIndex
- MCP
- Vercel AI SDK
- Ollama
Vector & data
- pgvector
- Qdrant
- Elasticsearch
- Redis
- Supabase
- MongoDB
Cloud AI
- AWS Bedrock
- Azure OpenAI
- Vertex AI
On-device
- Core ML
- ML Kit
- TensorFlow Lite
Quality & ops
- LangSmith
- Langfuse
- Datadog
Questions teams ask before adding AI.
How much does an AI project cost?
An AI audit starts from about $5,000, and a working pilot on your data usually costs $10,000–$25,000. A full integration depends on the number of features and systems; you get a detailed estimate after a free call. Model usage costs are estimated upfront and tracked per request.
Do we need to rebuild our app?
No. We add an AI layer next to your existing backend and connect it through APIs, so your app, design and users stay the same. Most features ship as an update to the current product.
Which AI model will you use?
The one that fits the task, budget and privacy rules — GPT, Claude, Gemini or open-source models like Llama and Mistral. Our setup lets you switch models later without rewriting the app.
Is our data safe?
Yes. We use enterprise APIs that do not train on your data, mask personal data, apply role-based access and can host models in your own cloud. We work under NDA and set up GDPR- and HIPAA-ready architectures.
How do you stop AI from making things up?
We ground answers in your own sources (RAG), show citations, test quality on real examples before release and add guardrails and human approval for sensitive actions.
Will I own the code?
Yes. You own all code, designs and IP from day one.
