Production-grade build, not another prototype.
Inflexion Analytics is a global data and AI consultancy. Our AI development and integration services build AI into the systems you already run: agentic workflows, RAG search, copilots and integrations, delivered by embedded engineers or a full squad.
Services in this stage
Five ways we turn a roadmap into working software.
A working build against your use case, fast.
Custom MCP connectors, plugins and APIs into your systems and data.
Claude built into the products and services your customers use.
Agentic workflows deployed into field services, education and more.
Move existing AI workloads from other models onto Claude.
How a build runs
1. Scope: agree the use case, success measures and integration points
2. Build: short cycles with working software to review every week
3. Harden: tests, monitoring, runbooks and Lead Engineer sign-off
4. Go live: release, hand over, and optionally move into managed services
What we build
Four disciplines in one delivery team.
Multi-step autonomous workflows, human-in-the-loop validation and MCP-based tool integration.
RAG pipelines and AI search, enterprise copilots and assistants, document and email parsing.
Custom APIs and systems, legacy ERP and CRM integration, on Claude, Gemini / Vertex AI and OpenAI.
Testing and deployment runbooks, Lead Engineer review on every release, live in 2–3 weeks.
Use cases
Typical builds by function, each scoped to one measurable outcome.
Ticket triage and dispatch, scheduling assistants, exception-handling agents.
Invoice and quote extraction, reconciliation support, forecasting assistants.
Lead research, proposal drafting, campaign content with approval steps.
Support copilots, knowledge search, case summarisation.
Contract, PDF and email parsing into structured data.
RAG search across policies, wikis and shared drives.
People stay in control, with human-in-the-loop checkpoints wherever an agent's action has real consequences. Every release is tested against evaluation sets and reviewed by a Lead Engineer, and access to your systems is least-privilege, with data handling agreed during scoping.
Models: Claude, Gemini / Vertex AI, OpenAI. Data platforms: BigQuery, Snowflake, Databricks, SAP. Integration: custom APIs, MCP connectors, ERP and CRM integration.
Who you work with
Builds are grounded in clean, well-structured data, so outputs hold up.
Engineering, data, integration and governance without juggling vendors.
Every build has an agreed success measure before work starts.
Systems fit your existing IT and analytics landscape.
Example engagements
Shipped an agentic copilot and RAG search into an existing SaaS product in one quarter, with an embedded 2-person squad.
Built a multi-agent workflow that automates ticket triage and dispatch across ERP and CRM, integrated via MCP.
Delivered a reference implementation on the vendor's platform for a flagship account, live in under 8 weeks.
FAQ
A first use case typically reaches production in 2–3 weeks once scope is agreed.
Yes. Most builds integrate with ERP, CRM and data platforms you already run, often via APIs or MCP.
Claude, Gemini / Vertex AI and OpenAI, chosen per use case.
You own it, or we keep it monitored and improving through managed services.
Next stage: AI Adoption & Managed Services. Keep it used, monitored and improving.
Explore adoption & managed services →