What we practise.
The practice was built inside large regulated enterprises, then applied to artificial intelligence in our own products. These are the disciplines we work in.
Seven disciplines.
Three in applied artificial intelligence, four in the enterprise data engineering and governance that makes the first three work.
Applied AI & agent engineering
AI agents that take action rather than only answer: tool and API wiring, scheduled and event-triggered runs, confidence thresholds, human handover, guardrails, and an audit trail showing why an agent did what it did.
Conversational AI
Chatbots and voice agents integrated into existing websites, phone numbers, and messaging channels, connected to the booking, CRM, or knowledge systems that let a conversation end in an outcome rather than a transcript.
Retrieval-grounded systems
Retrieval-augmented generation over your own records, with citations on every answer. Ingestion, chunking and embedding strategy, vector and hybrid search, multi-provider routing with failover, cost metering, and evaluation against real cases.
Enterprise data integration
Designing and operating the pipelines that move data between systems of record: extraction, transformation, reconciliation, and load, at production scale and on a schedule the business depends on.
Master data management
Establishing a single trusted version of core business entities across systems that disagree with one another. Matching, merging, survivorship rules, stewardship workflows, and the governance that keeps a golden record trustworthy over time.
Data governance, discovery & privacy
Locating and classifying sensitive data across an estate, mapping where it lives, and evidencing how it is handled. Retention and access review, and the controls required before customer records are exposed to an AI system.
Database & platform administration
Administration of relational and distributed data stores: performance tuning, backup and recovery design, capacity planning, access control, and the operational discipline required where downtime and data loss carry real cost.
Where the work was done.
The practice has worked in regulated industries where data accuracy is subject to external scrutiny.
Healthcare
Customer-facing data platform work in an environment governed by strict privacy and retention obligations.
Retail
Large-volume integration and master data work across merchandising and customer systems.
Financial services
Formal grounding in capital markets and global financial market structure.
Markets served
Work has been delivered for organisations in Texas, Illinois, Oregon, and Maine. Engagements are taken nationwide, delivered remotely as standard.
The platforms we work in.
We are a partner or a certified practitioner across the enterprise platforms our clients already run, so an engagement starts inside your existing stack rather than proposing to replace it.
BigID
PartnerData discovery, classification, and privacy governance. Finding sensitive data across an estate, mapping where it lives, and evidencing how it is handled. Increasingly the first question asked before any AI project touches customer records.
Informatica
CertifiedEnterprise data integration and master data management. Certified in PowerCenter administration and MDM administration, covering pipeline design and operation, matching and survivorship rules, and data stewardship workflow.
Oracle
CertifiedRelational database administration and development. Certified in database administration and SQL, covering performance tuning, backup and recovery design, capacity planning, and access control.
Alongside these, the practice works across the current applied-AI stack: multiple language-model providers, vector and hybrid search, and the voice, messaging, and payment platforms our own products run on in production. Certification and partner standing are verified directly with clients and counterparties on request.
How our software is built.
- Statically typed codebases with strict compiler settings throughout.
- Secrets held in managed environment configuration, never committed to source control.
- Payment card data handled exclusively by a PCI-compliant processor; card numbers never reach company systems.
- Least-privilege database access with separate service and public credentials.
- Graceful degradation on third-party failure, so no single provider outage takes a product down.
- Per-transaction usage logging, giving auditable unit economics.
- Customer-controlled spending caps enforced before a chargeable action occurs.
- Accessibility and mobile performance treated as acceptance criteria, not enhancements.
Consulting enquiries.
The company undertakes selective consulting engagements in data integration, master data management, and applied-AI implementation alongside its own product work.