Discover the real process
Map demand, failure points, data, controls, handoffs and the outcome worth changing.
AI engineering partner
A platform where it accelerates. Custom engineering where it differentiates.
retink.ai designs and builds AI-first systems: data processing and transformation, agentic applications, conversational experiences, MCP and WebMCP tools, APIs, integrations, analysis and the product surfaces people actually use.
Bring us the difficult systemEnd-to-end delivery
From unclear problem to operated capability.
We work at the boundary between product, data, operations and AI—the place where packaged software often leaves the hardest work behind.
Build the complete system
Product configuration, AI, custom applications, integrations, data pipelines, APIs, MCP and user experience.
Prove it under real conditions
Evaluation, simulation, security review, operational readiness and measurable baseline-to-outcome evidence.
Operate and improve
Release support, quality monitoring, workflow changes, agent tuning and a continuing data-to-action loop.
Six engineering practices
One team across product, data, integration and operation.
Engagement phases describe how we work. These practices describe what we build.
AI strategy & value
Use-case selection, operating design, baseline, business case and a sequenced route to proof.
Agentic systems & automation
Agents, tools, human gates and durable workflows that complete bounded work.
Data engineering & intelligence
Ingestion, transformation, analysis, vectors, data graphs, lineage and data-to-action systems.
Custom applications
Purpose-built web products, portals, conversational interfaces, SDK experiences and internal tools.
Integration & modernisation
APIs, OpenAPI, MCP, WebMCP, plugins, legacy adapters and cloud integration.
AI quality & improvement
Evaluation, simulation, monitoring, safety, cost, latency and evidence-led release improvement.
Conversational process applications
Turn any process into a guided, conversational application.
retink.ai combines dialogue, forms, grounded context, business rules, system actions and human collaboration. Use it for service, IT support, onboarding, investigations, employee processes or any journey that benefits from natural interaction without surrendering process control.
- Web, Microsoft Teams and service-workspace delivery
- Reusable flows, actions and external integrations
- AI-to-human transitions with complete context
- Custom interfaces through SDKs and packages
Data analysis and intelligence
Move from content ingestion to analysis and action.
Connect documents, files, databases, vectors, data graphs, conversations and operational evidence. Extract, transform, relate and analyse it with lineage intact—then expose trusted context and governed actions to agents, flows, analysts and applications.
- Ingestion, extraction, transformation and curation
- Vector retrieval, data graphs and structured analysis
- Source location, citations, versions and approval
- Signals that trigger real operational processes
Engineering surface
Modern technology, chosen for the work.
No forced model, cloud or integration dogma. Architecture follows security, latency, cost, data and operating constraints.
Agentic frameworksLLM + multimodal systemsConversational AIData pipelinesVector searchData graphsCustom web applicationsAPIs + OpenAPIMCP + WebMCPSDKs + WebPackagesCloud + private deploymentEvaluation + observability
Complex is acceptable. Vague is temporary.