We don't do generic. Each solution is shaped by the data, regulations and workflows of your sector. Select an industry to see how we approach it — and the results we've delivered.
Everything runs inside your compliance boundary — deployed on Azure or AWS within your own tenant, so PHI never leaves your environment. Models are evaluated against clinician-reviewed gold-standard datasets, and every generated note requires explicit clinician sign-off before it enters the record.
A privacy-first documentation assistant drafts clinical notes from consultation transcripts. Three failed pilots preceded us — the difference was enablement and strict data boundaries that earned clinical trust.
Deployed in-VPC on AWS Bedrock or Azure OpenAI with deterministic guardrails around every model call. Material actions pass through human approval gates, and each decision is logged with its source citations so auditors and regulators can trace exactly how a conclusion was reached.
A compliance-aware document agent reads, classifies and summarises loan applications — flagging risk and missing data before a human opens the file. We also told them where not to use AI, avoiding a seven-figure misstep.
Data is isolated per matter with privilege-aware access controls. Every answer cites the exact source passage so attorneys can verify before relying on it, and client data is never used to train any model. Outputs are framed as drafts for professional review, not legal advice.
A document-review assistant surfaces key clauses, anomalies and risks across thousands of documents, with citations back to the source — letting associates focus on judgement instead of search.
A hybrid edge-and-cloud architecture integrates directly with your ERP, MES and PLM systems. Sensor streams feed predictive models, while agents draft quotes and documents for human approval — keeping people in control of every commercial commitment.
A multi-agent system parses incoming RFQs, matches them to the product catalogue and drafts quotations — freeing the sales team to focus on relationships, not data entry. Live in 11 weeks from a messy data starting point.
RAG over your catalogue and reviews powers search and assistants, while a real-time personalisation layer adapts to each session. Everything is A/B-tested against conversion and revenue — not vanity metrics — and customer signals are handled with privacy by design.
Semantic search plus a shopping assistant helped customers find the right product faster, while a support agent deflected routine tickets — lifting revenue and cutting cost at the same time.
Our approach adapts to any regulated, data-rich sector. Tell us your domain and we'll show you what's possible.
Discuss Your Industry