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Work / 11 case studies

Enterprise AI, shipped.

Eleven systems across enterprise AI platforms, integration and cloud delivery, and products in production. Client work done through my agency is under NDA, so these case studies describe the problem, the architecture and my decisions. Names, data and screens stay private.

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Showing 11 case studies

  1. 01AI-Native Corporate Learning PlatformAn 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.An enterprise corporate-training providerDeliveredNDA
  2. 02Explainable AI Talent-Matching Platform for the Public SectorAn 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.A public employment programDeliveredNDA
  3. 03Adaptive AI-Readiness Assessment PlatformAn 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.A large enterprise groupDeliveredNDA
  4. 04AI Talent Assessment PlatformA 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.An enterprise HR-technology companyDeliveredNDA
  5. 05NextMovePath: An AI Strategy Engine for Canadian ImmigrationA live platform that turns a person's Canadian immigration profile into a personalised AI strategy report. Accurate calculations provide the facts, AI plans the strategy, and the report arrives live and as a PDF.CS2 Technologies productLive
  6. 06AgentlyLeads: An AI-Native CRM You Run from ChatGPT and ClaudeA CRM that teams operate straight from the AI assistant they already use. The AI prepares emails and updates, and a person approves anything that is sent, deleted or charged.CS2 Technologies productIn production
  7. 07From Spreadsheets to a Healthcare Compliance Platform with AIA 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.A UK-based cybersecurity and compliance advisory firmDeployedNDA
  8. 08Universal CRM Connector for an AI Calling AgentInstead of writing a separate integration for every CRM, I built one universal connector that lets an AI calling agent work with many CRMs, and delivered a full Jobber integration end to end.Call Agent AILive
  9. 09GWS Connect 24: Adding AI to a Live B2B MarketplaceAI added to a live wholesale marketplace: a 24/7 AI sales agent, deals sent to the CRM in one click with their activity shown back, and AI that drafts personalised outreach for a person to approve.CS2 Technologies productLive
  10. 10AI Lead Discovery on Reddit, With a Person Approving Every ReplyAn AI system that reads 56 Reddit communities for small business owners with real problems, drafts a helpful reply in the founder's voice, and sends it to Slack for a person to approve.An AI phone agent company serving small businessesLiveNDA
  11. 11HR and Payroll Platform: From Build to Secure Cloud in 11 DaysA full HR and payroll platform with an AI HR assistant, taken from a blank start to a secure, cloud-hosted product the client could test in about eleven days, through three changes of cloud plan.An enterprise HR-services companyDeliveredNDA

FAQ

Questions people ask first.

Can you integrate AI into an existing enterprise system?

Yes. I've added an AI sales agent, a CRM integration and human-approved outreach workflows to a live B2B marketplace, and an AI governance assistant to a running compliance platform. I work behind feature flags, fail softly at every integration boundary and test against production schemas before anything ships.

Do you build full AI platforms from scratch?

Yes. I've built multi-client AI platforms from scratch and delivered them to enterprise clients, owning the design, backend, frontend, AI, cloud infrastructure and automated deployments.

How do you handle data privacy and sovereignty?

Tenant isolation is enforced in the database with row-level security, PII is redacted before anything reaches a model, audit logs are append-only, and I deploy into the client's cloud and region. I've shipped a platform that builds and deploys inside an air-gapped environment.

How do you stop AI from making things up?

Code decides and the model explains. Scores, rankings and eligibility come from deterministic, tested code. The model drafts, grades against a rubric or writes the narrative, and its output is validated, has a fallback and can be overridden by a person.

Can you show client code or screens?

Not for NDA work. I describe the problem, the architecture and my decisions, and I'm happy to walk through the design on a call.

Where are you based and what hours do you work?

Pakistan (UTC+5), remote-first. I'm one hour ahead of the UAE, and my hours are flexible, so I overlap with teams in Canada, the US, the UK and Europe too.

Have you worked in my industry?

Maybe not yet, and that is rarely the hard part. I've shipped for HR technology, learning, the public sector, healthcare compliance, B2B sales, immigration and voice AI. What carries over is the engineering: keeping each customer's data apart, connecting to the tools you already use, checking AI output before it reaches anyone, and running it all reliably in the cloud. I spend the first days learning your domain and your data.