AI that handles document processing, decision routing, and data extraction. Measurable, auditable, and built for production.
Most organisations have run an AI pilot. Very few have shipped something their business can depend on in production. The gap is rarely the model itself — it is the surrounding engineering. Prompts drift. Outputs vary. There's no observability, no fallback, no way to audit what the AI decided and why.
We've built AI automation in environments where failure is not an option — financial services, healthcare, logistics. Every system we deploy includes evaluation frameworks, confidence thresholds, human-in-the-loop escalation paths, and full audit logging. The AI handles the volume; the infrastructure handles the trust.
We are model-agnostic by design. We evaluate GPT-4o, Claude, Gemini, open-source alternatives, and fine-tuned models against your specific task before recommending anything. The right model for your use case isn't always the most expensive one.
Every automation ships with evaluation suites, latency monitoring, cost tracking, confidence scoring, and fallback logic. Not bolted on — designed in from the architecture review.
We design escalation paths before we write a single prompt. Low-confidence outputs route to human review automatically. Your team stays in control of high-stakes decisions.
Every AI decision logged — input, output, model version, confidence score, and timestamps. Compliance-ready from day one, supporting ISO 27001, GDPR, and sector-specific frameworks.
We don't have preferred vendor agreements with OpenAI, Anthropic, or Google. We benchmark your actual task and recommend the model that performs best on your data, at your cost envelope.
We don't do pilots that never ship. Every engagement is scoped to reach production.
Automated extraction, classification, and validation of structured data from unstructured documents — invoices, contracts, forms, reports, medical records. Accuracy benchmarked against your actual document corpus before deployment.
Classify and route inbound requests — emails, support tickets, claims, applications — at scale without human reading queues. Intent detection, priority scoring, and automated assignment to the right team or workflow.
Retrieval-Augmented Generation over your internal knowledge base — policies, contracts, technical documentation, product catalogues. Staff find answers in seconds, not hours. Source-attributed, hallucination-resistant, access-controlled.
Multi-step AI agents that plan, execute, and verify complex workflows across your systems — CRM updates, data enrichment, report generation, compliance checks. Tool-calling pipelines with defined boundaries and full observability.
Internal copilots that augment your team's work — legal contract review, code generation, policy summarisation, customer-facing assistants. Built on your data, with guardrails that prevent hallucination and enforce brand voice.
For organisations earlier in the journey. We run a structured process audit, identify the highest-ROI automation opportunities in your business, prioritise by feasibility, and produce a 12-month AI roadmap with business cases.
The difference between a demo and a system your business depends on comes down to five engineering decisions made before the first prompt is written.
We build a labelled evaluation dataset from your real data before choosing a model. Every candidate model is benchmarked on your task — not on MMLU or HumanEval. Accuracy, latency, and cost are all measured before a line of production code is written.
Every AI decision carries a confidence score. Outputs below your defined threshold route to human review automatically — they never reach downstream systems silently. Fallback paths are designed and tested, not assumed.
Model performance dashboards, cost tracking, latency percentiles, and accuracy drift alerts are live from day one. You always know what the AI is doing, how well it's doing it, and what it's costing per decision.
Every AI decision is logged — input payload, model version, output, confidence score, routing decision, and timestamp. Logs are immutable and queryable. Regulators, auditors, and your own QA team can reconstruct any decision.
Prompts are versioned in Git like code. Every change runs against your evaluation suite before promotion to production. No silent prompt drift, no regression surprises after an update.
We hold no preferred vendor agreements with any model provider. Every recommendation is based solely on benchmark performance against your data and your cost requirements.
We interview your team, map your current workflows, and quantify the volume and cost of manual processes. Every automation candidate is scored on ROI potential, data availability, and technical feasibility before we commit to building anything.
We collect representative samples of your actual data, build an evaluation dataset, and benchmark candidate models. You see the accuracy, latency, and cost numbers before we write production code. No surprises post-deployment.
Pipeline development with staging environment, integration with your existing systems (ERP, CRM, ticketing, storage), fallback logic, audit logging, and monitoring dashboards. Full regression test suite before production promotion.
Phased rollout starting at a defined percentage of volume. Live monitoring of accuracy, throughput, and cost. Monthly model performance reviews and prompt optimisation included. We track ROI against the business case we built in phase one.
A logistics operator processing 1,200 supplier invoices per day across 14 currencies. Vision model extracts vendor, amounts, line items, and PO references. LLM validates against purchase orders, routes approvals, and posts to SAP — 94% straight-through with no human involvement.
An insurance carrier receiving 800+ inbound claims and enquiries per day. LLM classifies claim type, extracts policy references, scores urgency, and routes to the correct specialist team — reducing average time-to-first-action from 4.2 hours to 18 minutes.
KYC document processing, credit decision support, claims triage, regulatory report generation, and anti-fraud anomaly detection. FCA-aware architecture with full audit trails as standard across all deployments.
Clinical document summarisation, patient triage assistants, prior authorisation automation, and FHIR-integrated data pipelines. Every deployment reviewed against relevant clinical safety standards and CQC requirements.
Contract review and risk scoring, due diligence automation, matter research copilots, and billing narrative generation. Built for the privilege, confidentiality, and accuracy standards the legal profession demands.
Invoice and purchase order processing, quality control report analysis, supply chain anomaly detection, and field inspection automation. High-volume, low-latency pipelines that integrate with SAP, Oracle, and custom ERPs.
Customer service triage, product catalogue enrichment, returns processing automation, and review sentiment analysis at scale. Personalisation pipelines that feed recommendation engines with structured AI-extracted data.
Internal copilots for engineering and support teams, automated onboarding workflows, churn prediction pipelines, and customer-facing AI features built into your product. We build the AI layer your roadmap has been waiting for.
