01
AI Agent Systems
Design and build production AI agents that reason, retrieve information, use tools and complete complex workflows.
- Agent orchestration
- Multi-agent systems
- Tool calling
- Human-in-the-loop
- MCP integrations
- Agent evaluation
Global AI engineering agency
We build intelligent systems for companies around the world.
We help ambitious companies design, build and scale AI products, agent systems and modern software from strategy to production.
Working with teams across the US, Europe and beyond.
Userrequest · chat / api
AI Applicationproduct surface
Agent Runtimeplanner · router · state
- Models
- Knowledge
- Tools
- APIs
- Memory
- Human Approval
Evaluationquality · safety · cost
Productiontracing · monitoring
Model RouterKnowledge LayerTool GatewayTracing
- AI Agents
- Applied AI
- Automation
- AI Platforms
- Global Delivery
- Cloud Systems
- Product Engineering
- AI Strategy
01 / Services
From AI strategy to production systems.
Six ways we help companies design, build and operate intelligent software — separately or as one end-to-end engagement.
02
Applied AI Products
Turn modern AI capabilities into useful products, copilots, search experiences and intelligent applications.
- LLM applications
- AI copilots
- AI search
- Document intelligence
- Knowledge assistants
- Recommendation systems
03
AI Automation
Automate research, operations, support and internal workflows using AI combined with reliable software systems.
- Operations automation
- Support automation
- Research automation
- Document processing
- Data extraction
- Decision workflows
04
AI Platforms
Build shared infrastructure for models, retrieval, evaluation, observability and agent execution.
- Model gateways & routing
- RAG infrastructure
- Evaluation systems
- Tracing & observability
- Guardrails
- Developer SDKs
05
Custom Software
Build the applications, APIs, cloud services and platforms required around the AI layer.
- SaaS & web applications
- APIs & backend platforms
- Distributed systems
- Cloud infrastructure
- Data platforms
- Third-party integrations
06
AI Strategy
Define what to build, what to buy, how to architect the system and how to move from experiment to production.
- Opportunity assessment
- Technical discovery
- Architecture design
- Build-vs-buy analysis
- AI roadmaps
- Production readiness
Featured platform
The intelligence layer behind modern products.
Agents, models, knowledge, tools, evaluation and tracing — designed as one system so every request is observable, testable and safe to ship.
Agents support-agent
run · 2m ago- Status
- Healthy
- Latency
- 1.4s
- Model
- Auto Route
- Evaluation
- Passed
- Trace
- #A93F1
- 01Customer Requestchat · api
- 02Planner3 steps
- 03Retrieve Context12 chunks
- 04Select Modelauto route
- 05Execute Tools2 calls
- 06Evaluatepassed
- 07Return Result1.4s
Trace #A93F1
total 1.40s
- planner210ms
- retrieve_context320ms
- select_model30ms
- model.generate620ms
- tools.execute150ms
- evaluate70ms
Illustrative interface. Values shown are demo data, not client metrics.
Solutions
AI systems for real business problems.
We are not tied to one vertical. The same engineering discipline applies wherever intelligence needs to be reliable, secure and useful.
Enterprise Knowledge
Connect internal knowledge, documents and data to secure AI assistants and agent workflows.
Customer Experience
Build intelligent support, search and conversational experiences for customers.
Operations
Automate repetitive workflows across internal teams and operational systems.
Research & Intelligence
Build AI systems that collect, analyze, synthesize and act on large amounts of information.
Developer Platforms
Create shared AI infrastructure that multiple product and engineering teams can use.
AI-Native Products
Launch new products whose core experience depends on modern AI models and agent systems.
02 / How we work
A clear path from problem to production.
Four stages, each with concrete outputs. Enough structure to de-risk complex work, without slowing it down.
01 Discover
Understand the business problem, users, workflows, existing systems and constraints.
- Problem definition
- Success criteria
- System inventory
- Risk map
02 Architect
Define the technical approach, system boundaries, data flow, models, integrations and production architecture.
- Architecture design
- Model & tooling selection
- Data flow
- Delivery plan
03 Build
Develop the product using production-quality software engineering practices.
- Working software
- Evaluation suites
- Observability
- Documentation
04 Launch & Improve
Deploy, observe, evaluate and continuously improve the system based on real-world usage.
- Production deployment
- Monitoring
- Evaluation loops
- Iteration roadmap
Technical capabilities
Engineering across the full AI stack.
From agent orchestration and retrieval to the cloud infrastructure underneath — one team covers the whole system.
Agent Systems
- Agent orchestration
- Stateful workflows
- Tool calling
- Multi-agent systems
- Human-in-the-loop
- MCP integrations
- Structured outputs
- Agent memory
Applied AI
- LLM applications
- RAG
- Embeddings
- Vector search
- Hybrid retrieval
- Reranking
- AI search
- Document intelligence
AI Platform
- Model routing
- LLM gateways
- Evaluation systems
- Observability
- Tracing
- Prompt management
- AI reliability
- Developer SDKs
Software Engineering
- APIs
- Backend systems
- Distributed systems
- Event-driven systems
- Data platforms
- Cloud infrastructure
- Internal tools
- Web applications
Cloud & Production
- AWS
- Kubernetes
- Docker
- Terraform
- PostgreSQL
- Redis
- CI/CD
- OpenTelemetry
Why work with us
Beyond the prototype.
Built for production.
Demos are easy. Systems that stay reliable under real users, real data and real constraints are the work.
- 01
Senior Engineering
Architecture and implementation are approached with production reliability and long-term maintainability in mind.
- 02
AI + Software
We combine AI capabilities with the software engineering required to make them useful in real products.
- 03
Business-Aware Architecture
Technology decisions are guided by business constraints, security, cost, speed and future flexibility.
- 04
Global Collaboration
Structured communication and async-friendly workflows make distributed international collaboration practical.
Selected work
Representative systems we design and build.
Anonymised engagements that show the shape of the work. Detailed case studies are shared on request.
Enterprise Knowledge Agent
A permission-aware AI system designed to retrieve internal knowledge and support complex employee workflows.
- RAG
- Agent Systems
- Enterprise Search
- Access Control
AI Operations Platform
A multi-step automation platform designed to coordinate research, decision-making and operational actions.
- Agents
- Automation
- APIs
- Observability
Shared AI Developer Platform
A reusable internal platform for model access, retrieval, evaluation and agent orchestration.
- AI Platform
- Evaluation
- Model Routing
- Developer Infrastructure
Project examples are generalised and anonymised. No client names, metrics or logos are shown without permission.
Global delivery
Built to work across borders.
We work with distributed teams using clear technical ownership, structured communication and modern async collaboration.
- Clear technical ownership for every workstream
- Written decisions, architecture notes and demos
- Scheduled overlap for reviews and planning
- Async-first delivery across time zones
Available for global remote engagements.
North America
Overlap with US and Canadian working hours.
Europe
Overlap with UK and Central European working hours.
Asia-Pacific
Async-first collaboration with scheduled overlap.
Remote-first
Distributed delivery with clear technical ownership.
Engagement models
Flexible ways to work together.
Choose the shape that fits your team today. Engagements often evolve as the system and the relationship mature.
- 01
Project Delivery
A defined product, platform or AI system delivered from discovery through implementation and launch.
- 02
Embedded Engineering
Senior AI and software engineers work directly alongside the client's internal product and engineering teams.
- 03
Technical Advisory
Architecture, AI strategy and technical decision support for teams that already have implementation capacity.
- 04
Prototype to Production
Take an existing AI prototype and rebuild the architecture, evaluation and infrastructure required for production.
About
AI is becoming part of the software stack.
The difficult part is no longer simply calling a model. The difficult part is turning intelligence into reliable, secure and useful production systems.
That is what we build.
AI engineering. Agent systems. Software architecture.
Built for companies operating globally.
We focus on AI agent systems, applied AI products, AI automation, AI platform infrastructure and the custom software around them. Typical projects range from a focused proof of concept to a multi-quarter production platform. We also take on strategy and architecture engagements for teams that are deciding what to build.
Contact
Let's build something intelligent.
Tell us what you are building, what problem you are trying to solve, and where you need help.
Have an AI project worth building properly?
Let's turn the idea into a reliable production system.