Our Technology Partners
We design AI systems across Google Cloud, AWS, and Azure without vendor lock-in. We recommend solutions based on your specific requirements, not vendor preferences.
Our approach to partnerships
Platform-agnostic by design
We design AI systems across Google Cloud, AWS, and Azure without vendor lock-in. Teams work with both commercial models (Claude, GPT, Gemini) and open-source stacks, recommending solutions based on specific requirements rather than forcing all projects through one provider.
Built in production, not in slides
Systems operate in live environments handling real users, real data, and operational risk. We focus on reliability, observability, cost control, and maintainability.
No vendor lock-in
You retain ownership of data, models, and IP. Architecture designed around open APIs, containerised services, and portable systems so you can migrate if requirements change.
Platforms we deliver on
Google Cloud Platform
Best suited for: Google Workspace, EU data-residency, conversational and document-processing workloads
Multilingual chat systems handling tens of thousands of monthly conversations. Retrieval-augmented generation using Vertex AI, document processing with Document AI, agent-based workflows on Cloud Run, and analytics via BigQuery. This is our deepest platform and where we run the majority of production workloads.
Amazon Web Services
Best suited for: Existing AWS estates, serverless architectures, event-driven workflows
AI agents using Claude via Bedrock. Workflow orchestration with Lambda, Step Functions, and SQS. Serverless automation platforms, container-based services on ECS/EKS, and cost-optimised architectures.
Microsoft Azure
Best suited for: Microsoft 365/Teams/SharePoint environments, strict governance requirements
Teams and Microsoft 365 integrated assistants. Document intelligence systems, RAG architectures with Azure OpenAI, multi-modal systems (text, speech, vision), and secure enterprise deployments.
Anthropic (Claude)
Best suited for: Long-context reasoning, complex documents, multi-step workflows, safety-critical applications
Contract and policy analysis systems. Tool-using agents for operations, customer support assistants, and decision-support systems with structured reasoning.
OpenAI
Best suited for: Rapid prototyping, high-volume conversational systems, developer workflows
High-throughput chat systems. RAG pipelines using OpenAI embeddings, code generation and documentation tools, and domain-specific model tuning.
Open-source and self-hosted AI
Best suited for: Strict data-sovereignty, on-premise deployment, cost-controlled large-scale systems
Self-hosted conversational systems. Fine-tuned domain-specific models, GPU-optimised inference stacks, and hybrid architectures.
Requirements-driven selection
We select platforms based on your specific needs:
- Budget -- API costs, infrastructure, licences
- Compliance -- data residency, HIPAA, SOC 2, ISO 27001
- Existing infrastructure -- current cloud provider
- Performance needs -- latency, throughput, availability
- Data sensitivity -- cloud vs. on-premise
We're transparent about trade-offs: cost vs. performance, speed vs. accuracy, managed vs. self-hosted.
Staying current
The team maintains current skills through:
- Cloud Architecture certifications (AWS, Azure, Google Cloud)
- AI/ML Specialisations (AWS ML, Azure AI Engineer, Dialogflow CX)
- Ongoing training -- conferences, vendor programmes, experimentation
Certifications prove baseline knowledge. Production experience proves we can deliver.
Interested in partnering?
For platform providers interested in partnership, we evaluate based on client demand, technical capabilities, and production readiness.
Our selection criteria:
- Production-grade reliability (SLAs, uptime, support)
- Clear pricing (no hidden costs)
- Strong documentation and developer experience
- Compliance certifications (SOC 2, ISO, GDPR)
- Active roadmap and responsive support
Get in touch: [email protected]