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P. McCann Strain
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Legal tech and operations

Founder-Led Legal Infrastructure And Patent Intelligence

Datamise shows the operator side of Peter's engineering: a two-person team replacing fragmented legal operations with owned, auditable digital infrastructure. Praviar extends that pattern into AI-assisted pharmaceutical patent intelligence with a deliberately bounded public case study.

Patent intelligence support

Praviar

Current founder venture for pharmaceutical patent-intelligence support: deterministic checks, bounded AI assistance, and no public legal-opinion claim.

Two-person team

GMB equal-pay claims infrastructure

Owned claims infrastructure built for GMB equal-pay campaigns, replacing fragmented legal operations.

Profitable in year one

Founder-led full-stack delivery

Discovery, architecture, build, testing, deployment, training, and support.

Patent intelligence, not legal advice

Praviar is positioned as pharmaceutical patent-intelligence support: a tool for organising source material, surfacing risks, and keeping AI reasoning inside deterministic review boundaries.

  • The boundary is explicit: support for patent intelligence, not legal advice, a legal opinion, attorney replacement, or validity certification.
  • The public case study shows product judgement around regulated AI without exposing the protected operating details.
  • The work is presented as a current founder venture with demo video coming soon, not as a public customer-adoption or revenue claim.

The operational problem

Equal-pay claims involve fragmented records, inconsistent job titles, membership verification, signatures, contracts, and settlement calculations.

  • Structured digital collection replaced paper forms across GMB equal-pay campaigns from 2023.
  • Automated membership verification, contract generation, and e-signature formed an auditable chain from first claim to executed settlement.
  • GMB gained ownership of its claims data and workflows rather than depending on external vendors.

The engineering pattern

The work is legal infrastructure: controlled data capture, reproducible transformations, reviewable calculations, and clear operator workflows.

  • SettleMise turns equal-pay datasets into reviewable valuation schedules; it supports human review and does not decide liability.
  • New campaigns launch through configuration rather than a rebuild.

Auditing the platform itself

Datamise also audited GMB’s gold-standard Airtable base — the template cloned to every regional equal-pay campaign — and produced a prioritised remediation roadmap.

  • The audit produced 38 prioritised findings — 21 critical, 7 architecture, 10 hygiene — across 7 tables, 20 automations, and 3,835 records.
  • It identified data-loss-class script bugs that would fire on any regional clone, and traced fragile string-match joins reused across 9 of 13 scripts.
  • It set out a roadmap — linked records, a normalised Contracts child table, a consolidated validator — estimated at about 14 days to reach 2026 best practice.
“Datamise has set a gold standard in professionalism and exceptional software development. Their commitment to quality of work has been evident in every stage of the project, with top-notch solutions and attention to detail.”
Megan Fisher, GMB Union

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Related work

Read all writing

Praviar patent intelligence

Pharmaceutical patent-intelligence support with product boundaries and demo video coming soon.

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Digitising Equal Pay

Full article on the claims pipeline.

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SettleMise valuation engine

Reviewable equal-pay calculations, audit events, exports, and penny-level internal checks.

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AI engineer profile

How legal-tech delivery fits the broader engineering profile.

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About Peter

The longer story and contact details.

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