Category A · 7 services

Artificial Intelligence & Machine Learning

Deep AI engineering: models, agents, vision, and forecasting, built to survive production.

Most AI projects do not fail at the model. They fail at the retrieval layer that never had the right context, the evaluation nobody wrote, the guardrail nobody set, and the interface that put an unexplained number in front of a person who had to act on it. We build the whole system: the data that feeds it, the model that reasons over it, the harness that proves it is right, and the trace that explains it six months later.

What we build

A.1

Generative AI & Large Language Model Engineering

Retrieval, evaluation, and guardrails around a model you can defend

Production systems built on large language models, hosted or self-hosted. We build the retrieval layer over your own document estate with layout-aware parsing and hybrid search, prompt and context architecture that fits the task rather than the demo, evaluation suites that gate every change, guardrails that redact personal data before it reaches a model, and a model gateway that routes each call by cost, latency, and capability with automatic fallback.

RAG
Fine-tuning
Evaluations
Guardrails
Model routing
pgvector

What we build

A.2

Agentic AI Systems & Enterprise Copilots

Agents that hold a plan, call real systems, and stop where they should

Multi-step agent runtimes wired into the systems an organisation actually runs on. Tool and function-calling layers over internal APIs with a typed contract per tool, planner and executor loops with bounded retries, durable run state that survives a restart, policy checks and human approval gates on every irreversible action, token and cost budgets enforced per run rather than per request, and a replayable trace of every call an agent made.

MCP
Function calling
Durable execution
OpenTelemetry
RBAC
Approval gates

What we build

A.3

Computer Vision & Visual Inspection

Defect detection, site monitoring, and document capture at line rate

Vision pipelines that run at the speed of the process they watch. Detection, segmentation, and anomaly models trained on the small, imbalanced defect sets real production yields, deployment to edge accelerators and industrial GPUs, camera calibration and multi-view geometry, lighting-invariant preprocessing, drift monitoring against a golden set, and active-learning loops that route uncertain frames back to a human before they become a false accept.

ONNX
TensorRT
GigE Vision
Edge inference
Active learning
YOLO

What we build

A.4

Predictive Analytics & Decision Intelligence

Forecasts, anomalies, and optimisers that end in a decision

Systems that turn history into a decision rather than a dashboard. Probabilistic forecasting with calibrated prediction intervals, multivariate anomaly detection over operational telemetry, constrained optimisation and scheduling solvers, scenario simulation against assumptions that are written down and versioned, backtesting harnesses that score a model on the decision it would have made, and drift monitoring on every input distribution.

Probabilistic forecasting
MILP
Backtesting
Drift detection
Causal inference

What we build

A.5

Natural Language Processing & Document Intelligence

Retrieval that cites its source, across contracts, forms, and archives

Retrieval and extraction systems over document estates that were never designed to be queried. Layout-aware parsing of PDFs, scans, forms, and technical drawings, table and field extraction with per-field confidence, hybrid vector and lexical retrieval with cross-encoder re-ranking, chunking tuned to document structure rather than character count, answers bound to a citable source page, and incremental re-indexing as the corpus changes.

OCR
Hybrid retrieval
Re-ranking
Named entity recognition
Citations

What we build

A.6

MLOps & Machine Learning Platform Engineering

From notebook to production, with a path back when it goes wrong

The platform that lets a team ship models repeatedly rather than once. Feature stores with training and serving parity, experiment tracking and model registries, reproducible training pipelines, CI and CD for models with automated evaluation gates, canary and shadow deployment, GPU scheduling and cost control, and monitoring for data drift, concept drift, and quality regression in production.

MLflow
Kubeflow
Feature store
Model registry
Canary deployment
GPU scheduling

What we build

A.7

Conversational AI, Voice & Chat Systems

Speech and chat front ends that hand off cleanly to a person

Voice and text front ends over operational systems. Streaming speech recognition and synthesis with sub-second turn latency and barge-in, intent handling grounded in live system state rather than a scripted tree, multilingual and code-switched input handled inside one session, redaction of personal data before it reaches a model, escalation that hands a live conversation to a person with the full context, and transcript-level quality scoring.

Streaming ASR
TTS
Barge-in
PII redaction
Multilingual
SIP and telephony

What we build

How it connects

Inside ai & ml.

The systems in this area, and what each one hands to the next.

Generative AI & LLMs

Production systems built on large language models, hosted or self-hosted.

What we build

Agentic AI & Copilots

Multi-step agent runtimes wired into the systems an organisation actually runs on.

What we build

Computer Vision

Vision pipelines that run at the speed of the process they watch.

What we build

Predictive Analytics

Systems that turn history into a decision rather than a dashboard.

What we build

NLP & Document AI

Retrieval and extraction systems over document estates that were never designed to be queried.

What we build

MLOps Platforms

The platform that lets a team ship models repeatedly rather than once.

What we build

Conversational AI

Voice and text front ends over operational systems.

What we build

Bring us the whole problem.

Tell us where the work is stuck, whether that is a model that never reached production, an application nobody can change, a data platform nobody trusts, or a plant the business cannot see. An engineer replies with a first read, not a sales deck.