GreenM · Proposal — Data, AI & CQC Evidence
The Bristol Practice · Private GP · 07 Jul 2026 · GM-CQC-2026-BP · v2

Prepared for Dr Charlie Marshall & Dr Henry Hardy · The Bristol Practice · following our call, 7 July 2026

What we heard on Tuesday — and a two-month path to evidence that runs itself

Four GPs, a membership list of ~40 and growing, and a disproportionate share of founder time going to the regulatory side: policies done, audits and analytics now starting, and reports that Semble makes slow to get out. This page turns our conversation into a concrete scope, the terms we quoted, and next steps — written so you can review it with Henry.

The 30-second read

You told us
Regulatory work takes a disproportionate share of time. Getting audit and analytics data out of Semble is time-consuming. Much of the CQC evidence already exists — it needs tagging to the categories CQC wants. The same Claude/Gemini prompts are re-run by hand. Data handling must be airtight.
We propose
A two-month starter that stands up your AI Foundation — a private environment in your own UK cloud that runs AI requests internally — plus a Semble data connector, your existing evidence mapped to CQC's quality statements, and your repeated prompts turned into scheduled, anonymised workflows.
Terms quoted
$5,000/month for ≈100 hours (≈£3,700 at today's rate) during the starter; afterwards scale to need (ongoing support from ≈£1,000/month unless we're building new features). One month's notice either side. No software to license — expertise plus infrastructure you own.
Next step
Review with Henry. Alexey is in the Bristol area in about two weeks — happy to talk it through in person over a coffee.
Questions before you meet with Henry? Email Alexey

CQC rating

None yet

Registered

May 2025

Members

~40and growing

Clinicians

42 founders + 2 GPs

The bar
84%
Of the 861 GP practices holding a published rating under CQC's current framework in our dataset, 723 — 84% — are Good. A first assessment lands against a known, and high, bar.
What pulls practices under
2×
Safe (133 practices) and well-led (130) sit below Good more than twice as often as any other key question. Both are evidence-and-oversight disciplines — governance, not clinical surprises.
Direction of travel
Dec2026
As we discussed on the call: the CQC changes landing at the end of the year put still more weight on evidence that is collected and acted on continuously — pipelines, not binders assembled the week of the visit. We wrote up what changes in 2026 →

What we heard

Discovery call · 07 Jul 2026 · Charlie, Alexey, Nadya
Regulatory load

A disproportionate share of founder time

The CQC application is done; the work now is audits and data analytics as the patient list grows. In your words, it “takes up a lot of brain space” that belongs on clinical care and building the business.

The data bottleneck

Semble holds the data; reports are slow to produce

Clinical records live in Semble, policies in Practice Index. Extracting data for audits and CQC reporting is time-consuming — and much of the evidence already exists; it needs tagging to the categories CQC asks for.

The constraint we build to

Airtight data, anonymised in processing

The less that leaves, the better. Everything below runs inside your own UK-region cloud environment (Azure or AWS) — you hold the access; identifiable Semble data is minimised and anonymised before analysis; nothing trains anyone else's models.

One thing this proposal deliberately does not lean on: AI note-taking in consultations. You told us documenting is part of your clinical thinking, and that today's generated notes read wordy — so nothing here depends on scribing. The same foundation supports it later if any of the GPs wants it (one already uses Heidi), but it is not the plan.

The two-month starter — proposed scope

6 workstreams · sized for a founder-led practice

Each item traces to something you named on the call. The aim of the first two months is visible return — reports you stop producing by hand — plus a foundation every later use case reuses.

01

AI Foundation — a private environment in your own Azure or AWS space (UK region) that runs AI requests internally; you hold access and keys; aligned with GDPR and NHS DSPT by construction

Month 1Foundation
02

Semble connector — the extraction bottleneck removed. We built the same connector for another partner clinic, surfacing Semble data to their AI of choice

Month 1Proven before
03

Evidence map — inventory what you already have (Semble, Practice Index, policy drive) and tag it to CQC's quality statements, so gaps are visible and the pack is assessor-ready

Month 1–2Your words: “tag it in the right place”
04

Prompt workflows — the Claude/Gemini prompts you re-run by hand become scheduled, anonymised workflows on your infrastructure, with the model chosen per task and per cost

Month 2Quick ROI
05

Audit & analytics reports — recurring clinical-quality and audit reporting generated from Semble data: for evidence-based practice first, compliance as the byproduct

Month 2Recurring value
06

Monthly evidence report — collected automatically, actioned visibly, verifiable whenever CQC arrives; doubles as your internal governance review

Why continuous evidence — CQC's assessment model, explained →
OngoingFrom month 2
GreenM service

Private AI Foundation

A secure and compliant private AI infrastructure for healthcare — the productized pattern behind workstreams 01 + 04.

greenm.io/services/private-ai-foundation →
GreenM service

Unified Health Data

Clinical, financial and operational data in one AI-ready place — the productized pattern behind workstreams 02 + 05.

greenm.io/services/unified-health-data →

After the starter, the engagement scales to what you actually need — same named team stays attached, with a weekly check-in with Nadya Tolmacheva, our UK delivery lead.

We've built this before

3 live case studies · greenm.io

Three published projects that map onto this scope — click through for the full write-ups.

ROC Clinic · private clinic group

Unified data platform — reporting without the scramble

One data layer across clinical and operational data: manual reconciliation gone, real-time reporting, secure exports. The pattern behind workstreams 02 + 05.

“Month-end stopped being a scramble. The team now self-serves most answers.”

Read the case study →
NPH Group · UK occupational health

AI policy & document assistant — live in six weeks

Care teams get instant, accurate answers from their own policies, SOPs and operational documents. The evidence-map discipline of workstream 03.

“The AI policy assistant has already made a difference — our teams can find the information they need instantly.” — Mark Philpott, CEO

Read the case study →
Medefer · NHS security standards

AI letter-quality assessment with full auditability

AI review of clinical correspondence with clear metrics and governance, built to NHS security standards — the same airtight constraint workstreams 01 + 04 are built to.

“The AI-powered assessment has already helped standardize communication and improve review efficiency.”

Read the case study →

Terms, as quoted on the call

No software to license · expertise as a service
Starter
$5,000 per month for ≈100 hours of engineering and delivery time, for the first two months — ≈£3,700 at today's exchange rate. On the call we rounded to £3,500; billing is in USD, so the exact GBP figure moves with the rate.
After that
Ongoing support runs ≈£1,000 per month; it rises only when we're actively building new features together. Hours adjust with one month's notice.
Commitment
One month's notice, either side. Engagements typically run on a 6-month frame once rolling — but nothing locks you in beyond the notice period.
What you keep
Everything. The environment, the connectors, the workflows and the evidence base are built in your accounts — if we part ways, it all stays with the practice.

To recap

A two-month starter that stands up your AI Foundation — a private environment in your own UK cloud, running AI requests internally — connects Semble, maps the evidence you already have to CQC's quality statements, and turns the prompts and reports you run by hand into scheduled, anonymised workflows. $5,000 per month for ≈100 hours (≈£3,700 today), one month's notice either side, and everything we build sits in your accounts, so it stays with the practice. After the starter, ongoing support runs from ≈£1,000/month unless we're building new features together. Alexey is in the Bristol area in about two weeks — a coffee with you and Henry works as well as a call.

Alexey Litvin
CEO · GreenM
alexey@greenm.io

Nadya Tolmacheva
UK Delivery Lead · GreenM