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AI platform development

I build multi-tenant AI SaaS platforms from scratch, where AI is part of the production line: content generation, retrieval, agents, voice and grading. Each client's data is kept apart in the database itself, AI spending has limits, and a person can overrule the AI. I own the work from architecture to cloud deployment.

What I build

Platforms where AI does real work inside a secure system, several of them shared by many client organisations:

  • Content that writes itself, within limits. A multi-tenant AI learning platform turns a one-sentence training request into a full course, narrated videos and a matching quiz, in English and Arabic, with AI spending capped by policy.
  • Scores people can defend. On an AI psychometric assessment platform, an AI assistant drafts the test from a role description, and established scoring science, never the AI's opinion, decides every result.
  • Matching that explains itself. A job-matching platform that explains every match builds profiles from a CV through a short conversation, tailors resumes without inventing facts and runs in a locked-down, offline cloud environment.
  • Grading with a person in charge. An adaptive AI readiness assessment adjusts its questions to each answer, grades written responses with AI and sends any uncertain grade to a human reviewer.
  • AI inside a regulated practice. An AI assistant for healthcare compliance answers questions inside a platform where every client gets its own protected workspace and data is never mixed.

How an engagement runs

  1. Audit the requirements. I check the brief against reality in week one and log every decision you make.
  2. Design the boundaries. What code decides, what the model does, where a person signs off, and where the data lives.
  3. Build with proof. Tests, automated quality gates and live click-through checks from the first sprint.
  4. Ship and hand over. Cloud infrastructure written as code, a live deployment, and documentation your team can run with.

Built for trust

Row-level tenant isolation, role-based access, audit logs, personal data removed before it reaches a model, AI cost ceilings, accessibility to WCAG 2.2 AA, and a person who can overrule the AI on the decisions that matter. The platform does not stop at a demo: I take it from local to production in your cloud.

Case studies

  • An enterprise corporate-training providerDelivered

    AI-Native Corporate Learning Platform

    An enterprise learning platform where AI does the heavy lifting: it writes courses, produces narrated training videos and grades written answers, while managers stay in control and costs stay within limits.

    Learning and corporate training · NDA

  • A public employment programDelivered

    Explainable AI Talent-Matching Platform for the Public Sector

    An AI layer for a public employment program: it builds job-seeker profiles from CVs, tailors resumes without inventing anything, and matches people to jobs with scores anyone can understand and audit.

    Public sector employment · NDA

  • A large enterprise groupDelivered

    Adaptive AI-Readiness Assessment Platform

    An adaptive assessment that measures employees' AI skills, grades written answers with AI under strict safeguards, and gives everyone a personal learning path, while people review anything uncertain.

    Enterprise workforce and HR · NDA

  • An enterprise HR-technology companyDelivered

    AI Talent Assessment Platform

    A hiring assessment platform where recruiters create tests by describing the role, candidates take them securely, and every score comes from proven, auditable scoring methods rather than AI opinion.

    HR technology · NDA

  • A UK-based cybersecurity and compliance advisory firmDeployed

    From Spreadsheets to a Healthcare Compliance Platform with AI

    A spreadsheet-driven consulting practice turned into a secure, multi-client platform: separate workspaces for every client, one-click remediation plans, ongoing monitoring and an AI assistant that never mixes clients' data.

    Healthcare cybersecurity and compliance · NDA

Guides

AI platform development · FAQ

Questions people ask first.

Can one platform serve many client organisations safely?

Yes. On the learning platform each client's data is kept separate in the database itself, and on the healthcare compliance platform every client gets its own protected workspace, with an AI assistant that never mixes clients' data.

Does the AI decide people's scores?

Not on the platforms I build. On the AI psychometric assessment platform, an AI assistant drafts the test, and every score comes from established scoring science, never from the AI's opinion. On the adaptive readiness assessment, any uncertain AI grade goes to a human reviewer.

How do you keep AI costs under control?

I build cost limits into the structure rather than adding them later. On the learning platform, every AI request is measured and spending is capped per task, per client each month and per user, so a double-click can never charge twice.

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