AI & Automation
AI solutions
Real integrations — not demos. AI that ships behind authentication, reads your data securely, and shortens an actual workflow.
LLM agents, RAG over private data, computer vision, and ML pipelines — production-grade.
What's inside
Capabilities
LLM agents
Domain-specific assistants with tool access, audit logs, and guardrails. Not chatbots.
RAG over private data
Retrieval-augmented generation grounded in your knowledge base, with row-level access control.
Computer vision
Imaging, OCR, and detection pipelines — medical, retail, industrial.
ML pipelines
Training, evaluation, deployment, and monitoring — reproducible, version-controlled, observable.
AI integration
Drop AI features into existing apps without rewriting them. Behind auth, with rate limits.
Vibe-coding rescue
When the prototype your team Cursor'd together needs to actually ship, we make it scale.
How we deliver
A four-stage engagement.
-
01
Use-case sizing
We start with the workflow, not the model. If AI doesn't shorten the workflow we say so.
-
02
Data audit
What do we have, what can we use, what governance applies? Output: a data risk register.
-
03
Prototype
Three- to four-week prototype with measurable accuracy / latency / cost targets.
-
04
Productionise
Auth, rate limits, evals, monitoring, model fall-backs, and a per-user cost ceiling.
Why this matters
What you get with us.
Model-agnostic
OpenAI / Anthropic / Mistral / open-source — picked per task, swappable later.
Privacy-first
On-prem deployments and zero-retention vendor configurations supported.
Cost ceilings
Every AI feature ships with a per-user / per-tenant spend cap your CFO can defend.
Eval harnesses
You can tell whether the model got worse next week. We build the test suite for that.
Selected work
Real engagements, real outcomes.
Healthcare
A medical-imaging suite the field team actually use.
Cleaning up clinical workflows for UltraVision Medical — from imaging intake to reporting.
Read the case studyAI · Healthcare
AI clinical assistant, integrated end to end.
How we helped DrRobot ship an AI-assisted workflow that nurses adopt without training friction.
Read the case study
Hospitality
Short-stay platform, Dubai-grade.
Booking, operations and pricing for WeStayDubai — built to scale across new buildings.
Read the case studyFAQ
Common questions about this service.
-
Can you keep our data out of OpenAI / Anthropic / Google training?
Yes. We default to vendor zero-retention modes and document the configuration. Self-hosted open models are also on the menu.
-
How do you measure whether the AI is good enough?
Eval harness on day one — golden test set, measured accuracy + latency + cost. The model is "good enough" when those numbers cross your threshold.
-
Will the running costs surprise us?
No. Every AI feature ships with a per-user spend cap and a hard rate limit. Cost is visible in the same dashboard as latency.
-
How long does an AI integration take?
Prototype: 3–4 weeks. Production-ready integration: 8–14 weeks depending on data, auth, and compliance scope.
-
Can you deploy on-prem?
Yes — for healthcare and government workloads we routinely ship into customer-owned infra.
-
Do we own the prompts and the eval data?
Yes. Prompts, fine-tuning data, and evals are checked into your repo, not ours.
Let's talk
Tell us about your project.
Send the details through WhatsApp and we'll route it to the right person.
Trusted by founders across healthcare, hospitality and professional services. London HQ · Bilingual EN/AR delivery · NDA-friendly