We combine deep evaluation expertise with AI to deliver faster, rigorous insights for public policy — without sacrificing methodological integrity.
Evaluations are commissioned too late, delivered too slowly, and by the time findings emerge, the decisions have already been made without them.
Conventional evaluation methods weren't designed for the pace of modern policy cycles. By the time a report lands, the window for action has closed.
Commissioners need evidence that evolves with their services — not a single report, but a continuous stream of actionable insight.
Public money is spent on interventions whose impact remains unknown, and policy decisions are made without the evidence they need.
We are not a software platform, and we are not another technology company that underestimates the messiness of real-world policy. We understand the scepticism around AI and share it.
Our model is built on human expertise first, with AI where it genuinely adds speed and rigour — and not where it doesn't. Every engagement includes quality assurance throughout, not just at the end.
We work alongside clients to design evaluations that fit their context, deploying AI models where they genuinely add value.
AI supports data processing, pattern recognition, and rapid evidence synthesis — preserving human judgement for interviews, interpretation, and stakeholder engagement.
Every engagement includes a QA process throughout, ensuring methodological integrity at every stage.
Faster evidence that keeps pace with policy decision-making, so findings arrive when they're still needed.
Each evaluation follows a structured process that blends AI speed with human expertise — always clear about which is doing what.
Our AI scheduling assistant reaches out to your list of participants — stakeholders, service users, staff — and arranges interviews at times that work for them. No back-and-forth emails, no admin burden on your team. You provide the contacts, we handle the rest.
Before any interview takes place, our platform manages the paperwork. Participants receive consent forms, data handling agreements, and privacy notices automatically. Everything is logged and stored in line with GDPR, giving you a clear audit trail from day one.
This is where we stay deliberately human. Our evaluation specialists lead every interview themselves — building rapport, following up on nuance, and adapting in real time. We don't believe the most important conversations in an evaluation should be handed to a chatbot.
Interview recordings are transcribed and processed by AI on secure, GDPR-compliant servers. The system runs qualitative coding — identifying themes, patterns, and sentiment across your full dataset — at a speed and consistency that manual analysis can't match. Our team reviews and validates every output.
If you have other evidence — survey results, monitoring data, outcome metrics, case files — we feed it into the same analytical pipeline. This lets us triangulate findings across qualitative and quantitative sources, giving you a richer and more robust evidence base.
We synthesise everything into a clear, rigorous evaluation report designed for decision-makers. Findings are grounded in evidence, structured around your evaluation questions, and delivered in time to actually inform the decisions they were commissioned to support.
We combine what no technology firm and no traditional consultancy offers individually: methodological expertise, domain knowledge, and AI capability in a single integrated practice.
PhD researcher in Social Epidemiology at UCL and Research Fellow at RAND Europe. Deep expertise in evaluation methodology, health and social policy research, and evidence synthesis. Brings academic rigour, sector networks, and credibility with commissioners and funders.
MSci Physics student at UCL specialising in computational methods and machine learning. Specialist expertise in AI, data science, and applied machine learning. Ensures AI integration is robust, transparent, and appropriate.
Whether you're commissioning an evaluation or looking for faster, more useful evidence, we'd love to hear from you.
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