Fixed-Price Assessment
A scoped engagement with clear deliverables, timeline, and fixed cost. Ideal for initial assessments and proof-of-concept projects.
Data & AI
Data platforms and AI systems judged on whether they earn their cost, taken from proof of concept to production. We build the smallest architecture that serves the use case.
Use-case triage: value against readiness
A two-by-two triage: business value against production readiness. Typical placements: enterprise search and document processing rate build-now; workflow automation and data platforms need the path proven; a standalone copilot demo stays demo-only.
Use cases earn production by value, not by demo quality.
Most organizations have the data but lack the architecture to actually use it for forecasting, automation, or better decisions. Off-the-shelf AI tools rarely fit specific business processes, and without a solid data foundation, AI initiatives stall at the prototype stage and never reach production.
Our approach
We start from the decision or process the data is meant to serve, then design the platform to fit. We build in increments with your domain experts in the loop, and a use case only scales to production once its value is measured, with monitoring and governance in place.
- 01
Data landscape
Trace where the data lives, its quality and its owners, against the decisions and processes you want it to drive.
- 02
Fit-for-purpose platform
Design the smallest data and model architecture that serves the use case: RAG, custom LLM integration, or plain analytics.
- 03
Iterative build
Ship in validated increments with your domain experts in the loop, measuring output quality before widening scope.
- 04
Grounded operation
Monitor accuracy, cost per query, and drift; retrain and re-index on the schedule the business case supports.
Deliverables
- Data platform architecture and implementation plan
- AI/LLM proof-of-concept with business case validation
- RAG-powered enterprise search or knowledge base solution
- Production deployment with monitoring and feedback loops
- AI governance framework and model performance reporting
Technologies & certifications
Technologies
- Azure OpenAI
- LangChain
- Azure AI Search
- Databricks
- Power BI
Engagement options
Three ways to work with us. The problem decides which fits.
T&M Consulting
Time-and-materials engagement for ongoing advisory, architecture reviews, and implementation support.
Continued support
A defined, renewable support period after handover. We stay to see it through, until your team no longer needs us.
Frequently asked questions
- What AI/LLM platforms do you work with?
- We primarily work with Azure OpenAI Service, but also support AWS Bedrock and open-source models. Our vendor-neutral approach means we recommend the best fit for your use case, data governance requirements, and budget.
- Can you build a RAG solution for our internal knowledge base?
- Yes, RAG (Retrieval-Augmented Generation) for enterprise search is one of our core offerings. We design the pipeline, configure Azure AI Search, and tune retrieval, ranking, prompts, and evaluation to deliver accurate, source-cited answers from your own documents.
- How do you handle AI data privacy?
- We comply with applicable data protection regulations (GDPR, APPI, and others). We configure data pipelines to keep sensitive information within approved regions, implement access controls, and establish AI governance frameworks that meet international standards.
- What does a typical AI PoC look like?
- A typical proof-of-concept runs 2-4 weeks. We define 1-2 high-value use cases, build a working prototype, validate business impact with real data, and deliver a go/no-go recommendation with a full production roadmap.
Talk it through
Tell us about your environment and goals. We'll outline a practical path forward.
Discuss your AI needs
Response: within one business day