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Clinical Data Harmonization
A healthcare / clinical research organization needed to harmonize complex source datasets into a standardized data model for downstream analytics, reporting, and…
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We design, engineer and deploy secure RAG platforms, AI agents and intelligent applications, integrated with your data, systems and teams.
AI engineering capabilities
From retrieval and fine-tuning to data harmonization and MLOps: the techniques behind our production AI systems, and the product engineering around them.
Featured work
Production RAG, document AI and data platforms delivered for healthcare, finance and construction teams.
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01
A healthcare / clinical research organization needed to harmonize complex source datasets into a standardized data model for downstream analytics, reporting, and…
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02
FinSight AI was developed as a POC for a CA and finance advisory team that needed a faster, more affordable, and more…
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03
A construction technology platform was built for trade contractors, general contractors, design teams, and project managers to simplify the submittal workflow. In…
Read case studyIndustries & domains
We combine domain context with AI engineering to solve the workflows, data and operating challenges specific to your sector.
Secure AI for knowledge, operations and digital experiences.
Explore domainControlled AI for customer, compliance and operational workflows.
Explore domainIntelligent hiring, talent and employee experiences.
Explore domainPersonalised learning, assessment and academic operations.
Explore domainCopilots, agents and automation embedded into digital products.
Explore domainDocument intelligence and AI applications for engineering firms and project teams.
Explore domainHow we work
We understand your business problem, shape the right AI solution, connect it with your systems and take it securely into production.
We define the workflow, users, available data, constraints and measurable outcome.
We shape the AI approach, architecture, integrations, controls and human review points.
We build the solution and connect it with the data, applications and workflows your team uses.
We launch securely, monitor quality, cost and risk, and improve the system with real usage.
Senior specialists stay involved from use-case selection to handover.
AI, data and product engineering in one delivery team.
Security, evaluation and monitoring designed in before scale.
Prove value on a real workflow before expanding it.
Client perspective
AI DISCOVERY ENGAGEMENT
One focused engagement to assess your business workflows, compare 5–7 candidate opportunities and recommend the first workflow worth funding.
Up to 3 functions and 5–7 candidate workflows.
Value, feasibility, readiness, controls and risk.
Executive Direction in 48 hours; complete package within 5 business days.

Start with a practical first phase
Share the problem, current tools and expected outcome. We’ll recommend a sensible first phase with scope, timeline and next steps.
Common questions
AI strategy, RAG and knowledge systems, agent workflows, data and ML engineering, AI-enabled products and supporting web or mobile product development.
Most engagements start with a fixed-scope discovery or prototype phase, so you see value before committing to a full build. We’ll propose a clear scope and estimate within 24-48 business hours of your brief.
Discovery typically takes 5-10 days, a focused prototype 2-3 weeks and a production build around 4-8 weeks depending on integrations and scope.
Yes. We design around existing databases, document stores, APIs, cloud platforms, CRM, ERP and business applications.
We use test datasets, grounded-answer checks, monitoring, role-based access, guardrails, human approvals and audit logs according to the risk level.
Ownership, licensing and handover terms are documented in the engagement agreement. Custom code and deliverables are normally transferred as specified in the contract.