Feasibility & Data Assessment
A review of data readiness, constraints, and technical risk before a single line of model code is written.
Feasibility • Validation • Delivery
AI Proof of Concept
Services
Research-driven PoC engagements that turn an AI ambition into evidence — feasibility, benchmarks, and a working prototype you can put in front of stakeholders.
Engagement at a Glance
From question to evidence
01
Scope & Success Criteria
Define the use case and the bar for success
02
Data & Feasibility
Assess data readiness and technical risk
03
Build & Evaluate
Implement the prototype and benchmark it
04
Findings & Demo
Document results with a demo-ready build
Clear scope, documented outcomes
What You Get
What Every PoC Delivers
Every engagement closes with artefacts your team can act on — not a slide deck of promises.
Working Prototype
A functional, demo-ready implementation of the highest-value use case, built on your data and your constraints.
Evaluation Report
Benchmarks, metrics, failure cases, and limitations documented with clear, honest recommendations.
Scale Roadmap
Prioritised next steps covering production readiness, cost, governance, and the path beyond the PoC.
The Catalog
Published Proof of Concepts
Each entry is a documented experiment: the problem it addressed, how it was evaluated, and what the results mean for the next investment decision.
2 services
AI PoC03 Oct 2026
Document Intelligence PoC
A proof of concept for extracting, classifying, and summarizing information from PDFs, invoices, contracts, and other business documents.
Discuss This PoCAI PoC
02 Oct 2026
AI Customer Support PoC
Build and validate an AI-powered customer support assistant that can answer common questions, search knowledge bases, and assist support teams.
Discuss This PoCAI PoC Methodology
A structured, research-driven path from idea to impact
Every engagement follows a transparent framework designed to reduce uncertainty before full-scale investment.
01
Problem Definition
Understand business or research objectives and define measurable outcomes.
02
Data Readiness Assessment
Assess data quality, gaps, availability, and technical feasibility.
03
Model Design & Experimentation
Select algorithms, design experiments, and test technical approaches.
04
Benchmarking & Evaluation
Measure performance using meaningful metrics and validation methods.
05
Performance Report
Deliver detailed insights, findings, limitations, and recommendations.
06
Investor / Demo-Ready Prototype
Build a functional PoC ready for stakeholders, demonstrations, and investment conversations.
Ways to Engage
How We Work With You
The same disciplined path every time: define, build, measure, document — with a decision at the end of each stage.
01
Discovery Sprint
A short, structured diagnosis that decides whether a PoC is worth building before budget is committed.
- Use-case framing
- Data readiness review
- Go / no-go recommendation
02
PoC Build
End-to-end design, implementation, and evaluation of a working prototype against agreed success criteria.
- Solution design
- Prototype development
- Benchmarked evaluation
03
Review & Roadmap
An independent evaluation of an existing prototype, internal experiment, or vendor proposal.
- Technical review
- Risk & cost analysis
- Prioritised roadmap
Every engagement closes with a written findings report and a recommended next step.
Discuss Your Use CaseStart With Evidence
Ready to Prove Your AI Idea?
Bring us a use case and a question. We return a documented answer: feasibility, benchmarks, and a prototype your stakeholders can actually see running.