Your demo ran on a clean prompt and one happy path. Production runs on real customer data, edge cases your test set never saw, and a cost bill that scales with every user. The gap between the two is where most AI projects quietly die.
Service AI solutions · nine production patterns · UK senior-only studio
AI solutions audited at the eval. gate, not the demo.
Three lines of OpenAI buys you a great demo. Production needs the other two hundred. Nine AI solutions for UK SaaS, fintech, and B2B teams — each one leaves with idempotent tool calls, an audit log per inference, and the SOC 2 evidence your enterprise prospect asks about.
24hreply, from a senior
200+projects shipped since 2019
Senioronly, on the spine
(Why CTOs sign with us for AI)
Three lines of OpenAI gets you a great demo. Production needs the other two hundred.
You don’t need a prompt. You need the eval gate, the audit log, and the off-switch that keeps your AI defensible the day a regulator, a VC, or your biggest customer asks how it works.
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What separates a demo from an AI solutionthe demo ships Friday · the complaint lands Monday
The demo always works. The production system is where the two hundred live.
We close that gap with the same spine on every build. An eval gold set gated in CI so a regression breaks the build, not your customer. An audit log per inference: model version, input, output, user, timestamp. A gateway so you swap providers in config when one doubles its price.
This page is the hub for nine AI solutions. Pick the one that matches what you’re building. Each has its own page, its own worked numbers, and a named founder we built it for.
Pick your AI build. Each page has a named protagonist.
Nine production AI patterns. One senior studio. Open any row, then take the full page.
AI features into the SaaS your customers already pay for. No rebuild, no lock-in.
Production agents on LangGraph + Claude + GPT-5. State machines, not weekend hacks.
Brand-tuned RAG chatbots with citation gates. No citation, no answer.
AI-powered workflow automation for UK ops and finance teams. Hours back per week.
Strict json_schema, idempotent tool calls, Azure EU Data Zone where you need it.
Bedrock + MCP + tiered routing + audit log. Opus, Sonnet, and Haiku per task.
LangChain + LangGraph that survives the move out of the notebook into production.
Retrieval with re-ranking, freshness windows, and citations your auditor can read.
AI-first product with eval gates and the AI off-switch your fifth VC asks about.
WHAT SHIPS AT EVERY HANDOVER
Procurement, security, and trust. What your CFO, CTO, and DPO see in writing
Every AI solution leaves with the same evidence pack. The pack your enterprise prospect’s 60-page questionnaire is really asking for.
SOC 2 Type II + evidence pipeline
SOC 2 Type II achieved at Empyreal in December 2025. Vanta or Drata evidence pipeline wired on day one for your build.
Signed DPA + SCCs
UK and EU GDPR-aware DPA. SCCs for cross-border. A versioned, procurement-tested sub-processor list before week one.
DSAR runbook + erasure
A 30-day DSAR response you can defend. Right-to-erasure at the schema. ICO audit-defendable from the first inference.
30-day walk-away, both ways
You keep everything. IP assigns on commit. SIG-Lite and CAIQ pre-filled, pen-test report, DR plan, and SLA in the pack.
The pain. The architectural answer.
Each one decides whether your AI survives the next VC question, the next price hike, or the next 10× in scale.
- 01
“What’s our product if we turn the AI off tomorrow? We don’t have an answer.”
Data + UX moat first, model second. Your data is the defensibility. Models route through the gateway. If OpenAI vanished, the product still works on Claude or self-hosted Llama.
- 02
“We can’t tell if a new prompt is better. We deploy and hope.”
Eval gold set + CI gating. 100-300 tasks with known answers. CI blocks a deploy that regresses more than 5%. Quality stops being a feeling and starts being a number.
- 03
“OpenAI doubled prices and we just had to swallow it.”
Multi-model gateway, swap in config. Swap GPT-5 to Claude to Gemini to self-hosted Llama with a config change, verified against your gold set before cutover. Done four times in 2025.
- 04
“We make money at 50 customers and lose money at 500.”
Per-task routing + cost discipline. Haiku for 60%, Sonnet for 35%, Opus for 5%. Same UX, a quarter of the cost per call. Median gross margin post-discipline: 81% vs 24% before.
- 05
“The AI invented a customer policy. Now we have a real complaint.”
RAG with citations + confidence threshold. No citation, no answer. Confidence threshold escalates to a human. Replay any production hallucination, add it to the gold set so it never repeats.
- 06
“How do we prove what the AI did when an auditor asks?”
Audit log per inference. Model version, input, output, user, timestamp on every call. Exportable, searchable, read-only. Your auditor reads the log and asks no more questions.
- 07
“Will the provider train on our customers’ data?”
Zero-retention tier + PII redaction. Zero-retention by default on every provider. PII redaction at the gateway. For regulated data we self-host Llama or Mixtral on your VPC. DPA before week one.
- 08
“The demo is beautiful, but it can’t handle a real customer load.”
Production-shape architecture from week one. RAG, gateway, evals, observability built in week two. The demo is the production system, just with fewer customers. No “rebuild for launch” sprint.
The stack we ship every AI solution on.
MERN for the product surface, Python for inference and evals, and the AI infrastructure layer that keeps the unit economics working at scale.
T1
What we build every AI solution on
MERN + PythonMongoDBExpress.jsReact + Next.jsNode.jsPythonTypeScriptAnthropic ClaudeOpenAI GPT-5PineconeLangChain / LangGraphMixpanelStripe
T2
When your AI brief calls for it
reach when neededLlama / MixtralWeaviate / QdrantPostgreSQL + pgvectorApache SparkFastAPIHuggingFace
T3
The cloud + infra
AWS-defaultAWSAWS BedrockAWS LambdaAWS SageMakerKubernetes (EKS)DockerRedisApache KafkaTerraformDatadog + SentryLangSmithMCP servers
Scale + receipts
The numbers your CFO,
The numbers your CFO,
your VC, and your acquirer ask about
The receipts that survive Series B diligence, in numbers not adjectives. Same senior engineers sign, ship, and maintain every AI build. SOC 2 Type II achieved at Empyreal in December 2025, with a held pen test.
Production scale
£540M+
Cumulative GMV through code we shipped
320M+
API calls a year on our 2025 code
Diligence record
12
Series A founders who raised Series B
2
Clients reached IPO. Three M&A exits
Trust + tenure
0
Customer-data breaches in seven years
96%
Engineer retention. Same seniors stay
Start with the audit. Then build.
Pick the engagement that fits where you are. Most teams begin with the 5-day audit, then move into a fixed-scope build.
The £8K 5-day audit
5 days, fixed price. It ends with the right pattern named, the eval plan drawn, and a fixed-scope quote in writing.
- The right one of nine patterns named
- Eval gold-set plan, 100 to 300 tasks
- Unit economics modelled at 100× scale
- Fixed-scope quote, no “starting at”
The fixed-scope build
Most inner builds run from £18K to £28K, fixed scope, 4 to 6 weeks. The demo is the production system from week one.
- Eval gates wired into CI
- Audit log per inference
- Multi-model gateway, swap in config
- Evidence pack at handover
The advisory retainer
Same seniors stay on to maintain, extend, and defend the build. Pause with 14 days’ notice, resume with 14 days’ notice.
- Same senior engineers, no handoff
- Gold set grows with production
- Provider swaps verified before cutover
- SOC 2 evidence kept current
“This page is the hub for nine AI solutions. Pick the one that matches what you’re building. Each has its own page, its own worked numbers, and a named founder we built it for.”
— Mohit, founder & reviewer on every PRWhat AI-founders actually ask before signing
Pain-first, soft-second.
Send a 5-line brief and we’ll tell you in the reply. Most teams who say “we need an AI agent” need AI integration into the SaaS they already have. Most who say “we need a chatbot” need RAG architecture underneath it. The £8K 5-day audit ends with the right pattern named, not the one you walked in asking for.
Both, behind a gateway. Sonnet for default reasoning and tone, Haiku for cheap routing and classification, Opus for the weekly heavy lift, GPT-5 for vision, voice, and image. The gateway routes per task, so you never depend on one provider. If one doubles prices or deprecates an endpoint, you flip a config flag.
The eval gold set. We build 100-300 representative tasks with your team in week one. Every PR runs against it. Quality is a number you both track. You launch when the number says it’s ready, not when the team feels brave. The number ships with the runbook.
Zero-retention tier on every hosted provider by default. PII redaction at the gateway. For regulated data we self-host Llama or Mixtral on your VPC. Signed DPA and sub-processor list before week one. Every audit our AI solutions have faced has passed.
It starts with the £8K fixed 5-day audit, which ends with a named pattern and a fixed-scope quote. Most inner builds run from £18K to £28K, fixed scope, 4 to 6 weeks. Bigger AI product builds run higher and we say so up front. You see the range and the duration before you commit, never “starting at”.
We model unit economics at 100× current scale on day one. Cost-per-call × calls-per-user × users. If your subscription is £49 and AI cost is £9.20 per user a month, you have 81% gross margin. If those numbers don’t work, we tell you in the audit, not in week ten.
Every project has two senior engineers paired, not one. Every decision goes into an ADR the same day. Mohit reviews every PR. In seven years, two engineers have left mid-project. Both handovers were inside 48 hours.
Yes, with 14 days’ notice. Engineers move to other projects, spend pauses, and you resume with 14 days’ notice. No cancellation fee. Done six times in 2025.
In context
What it looks like shipped.
ai solutions, in context — the dashboards, flows and components your team actually ships, reviews and maintains.
One paragraph. That’s it.
Tell us the use case, your model preference if you have one, your regulatory environment, and your deadline. Mohit replies inside 24 hours with availability and the next 5-day AI audit slot.
What happens after the email lands
- < 24h
A personal reply.
Yes, no, or the one question that decides which of the nine you need.
- Day 5
The £8K audit.
The right pattern named, the eval plan drawn, the fixed-scope quote in writing.
- Wk 6
A shipped AI solution.
Eval-gated, audit-logged, and the evidence pack your enterprise prospect reads.