AI Development

AI that earns its place in your business.

We design, build and deploy production-grade AI — from custom models and generative AI to computer vision and copilots — wired into the systems you already run, with security, evaluation and human oversight built in.

Book a free consultation → View AI work →
30+
AI & vision builds
10+
Years in software
10+
Countries served
6
Core AI capabilities
What We Build

The full span of applied AI.

Six capabilities that cover the AI work most teams actually need — chosen for the problem, not the hype.

Custom AI & ML

Bespoke models for prediction, scoring, recommendation and classification — trained on your data and tuned to the metric that matters to your business.

Forecasting Recommendation Risk Scoring NLP

Generative AI & LLMs

RAG assistants, copilots and content engines on top of leading LLMs — grounded in your knowledge base, with guardrails and evaluation so answers stay trustworthy.

RAG Fine-tuning Prompt Eng. Guardrails

Computer Vision & Spatial

Detection, tracking, OCR, body and pose estimation, and LiDAR-based 3D capture — turning camera and sensor data into decisions and measurable models.

Detection Pose / Body OCR LiDAR 3D

AI Agents & Copilots

Task and workflow agents that take action across your tools — with approvals, audit trails and a human in the loop wherever the stakes are high.

Workflow Agents Tool Use Approvals Human-in-the-Loop

MLOps & Data Engineering

Pipelines, feature stores, training and deployment that keep models reproducible, monitored and continuously improving — not stuck in a notebook.

Pipelines Feature Store Monitoring CI / CD

AI Integration

Drop AI into the products and workflows you already run — through clean APIs and SDKs, deployed to your cloud or on-prem with security baked in.

APIs SDKs Cloud / On-prem Security
Applied In Your Industry

AI pointed at real problems.

The same capabilities, shaped to the workflows, data and regulations of the sectors we build for.

Banking & Fintech

  • Real-time fraud and transaction risk scoring
  • Document AI for KYC, statements and underwriting
  • Support copilots grounded in policy and product docs

Healthcare

  • Claims and pre-authorisation automation
  • Clinical document extraction and summarisation
  • Triage and scheduling assistants with human oversight

Retail & E-Commerce

  • Personalised recommendations and semantic search
  • Demand forecasting and inventory optimisation
  • Product content generation and enrichment

Operations & Back-Office

  • Workflow agents that action tasks across your tools
  • Knowledge assistants over your internal documents
  • Computer vision for inspection, counting and QA
How We Deliver

From idea to production, safely.

A pragmatic path that proves value early and never skips evaluation or oversight.

01

Discover & map

We pin down the use case, the data and the success metric — and whether AI is even the right tool for the job.

02

Data & prototype

We prepare data and stand up a working prototype fast, so you see real outputs before committing to a full build.

03

Build & evaluate

We engineer the model and the app around it, and evaluate rigorously for accuracy, bias, safety and cost.

04

Deploy & improve

We ship to production with monitoring, guardrails and a feedback loop that keeps the system improving over time.

AI & Vision Work

Shipped, on real devices.

A few of the AI, computer-vision and spatial builds we’ve put in people’s hands.

iOS · AR
Body Tracking

AR Motion Arcade

15 full-body AR mini-games scored live from 30+ tracked body joints — pure on-device vision, no wearables.

View case study
iOS · LiDAR
3D Capture

LiDAR 3D Capture

Turns the iPhone LiDAR sensor into a handheld 3D scanner — textured, measurable models exported in seconds.

View case study
iOS · LiDAR
Spatial AI

LiDAR Floor-Plan Scanner

Walk a space and generate an accurate, editable floor plan with room dimensions — on-device, in minutes.

View case study
Our AI Stack

Proven tools, chosen on merit.

Models & Frameworks
PyTorch TensorFlow scikit-learn Hugging Face LangChain OpenCV ONNX Core ML ARKit
Data, MLOps & Cloud
Python Kafka Airflow MLflow Docker Kubernetes AWS Azure GCP
FAQ

Questions, answered straight.

How long does an AI project take?

A focused prototype is usually 3–6 weeks. A production rollout depends on your data and integrations — typically 2–4 months — and we ship in stages so you see value along the way.

Do we need our own data?

It helps, but it isn’t always required. We can start from your data, public or synthetic data, or pre-trained models and foundation LLMs — then improve accuracy as real usage data accumulates.

How do you handle accuracy and hallucination?

Every model is evaluated against a held-out set and your business metrics. For generative AI we add retrieval grounding and guardrails, and we keep a human in the loop on high-stakes decisions.

Is our data secure?

Yes. We deploy in your cloud or on-prem, follow least-privilege access, encrypt data in transit and at rest, and sign an NDA before we touch anything sensitive. We’re ISO 27001 certified.

Can you integrate AI into our existing product?

That’s most of what we do. We add AI through clean APIs and SDKs into your current stack, with staged rollout and feature flags so nothing breaks for your users.

What engagement models do you offer?

A fixed-scope build, a dedicated AI team, or staff augmentation — see Hire Developers, or book a consultation and we’ll recommend the right fit.

Insights

Related Insights

How our engineers think about problems like these.

All insights →

Have an AI idea? Let’s pressure-test it.

Bring us the problem — we’ll tell you honestly whether AI is the right tool, and map the fastest path to something real.

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