Hadi T.

𝐅𝐨𝐫𝐛𝐞𝐬 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐂𝐨𝐮𝐧𝐜𝐢𝐥 𝐦𝐞𝐦𝐛𝐞𝐫, 𝐇𝐚𝐫𝐯𝐚𝐫𝐝 𝐬𝐩𝐞𝐚𝐤𝐞𝐫, 𝐑𝐢𝐜𝐞 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐒𝐜𝐢𝐞𝐧𝐜𝐞. 𝐍𝐨𝐧𝐞 𝐨𝐟 𝐰𝐡𝐢𝐜𝐡 𝐦𝐚𝐭𝐭𝐞𝐫𝐬 𝐚𝐬 𝐦𝐮𝐜𝐡 𝐚𝐬 𝐭𝐡𝐞 𝐟𝐚𝐜𝐭 𝐭𝐡𝐚𝐭 𝐭𝐡𝐞 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐈 𝐛𝐮𝐢𝐥𝐝 𝐫𝐮𝐧 𝐢𝐧 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐮𝐧𝐝𝐞𝐫 𝐚 𝐫𝐞𝐠𝐮𝐥𝐚𝐭𝐨𝐫. Your compliance team keeps saying no to AI. I build the version they can say yes to. AI automation, generative AI, machine learning and EHR integration that run inside your own AWS or Azure account, so your patient, financial and proprietary data never leaves your control. An assistant I built is used by 500,000 employees. Credit desks run private AI I deployed where transaction data can’t leave the firm. Healthcare groups run it under HIPAA, with PHI staying inside the boundary at every step. What these have in common isn’t the model. In every one of them, a failure is a regulatory event, not a bug report. 𝐖𝐇𝐀𝐓 𝐘𝐎𝐔 𝐆𝐄𝐓 AI in production that your compliance team, auditors and board can review and approve. Access control, customer-managed encryption keys, private endpoints, data residency controls and audit logging on every call are designed in from day one, built to pass a HIPAA or SOC 2 review instead of being retrofitted when an auditor asks. And automation that gives your team hours back every week. 𝐇𝐎𝐖 𝐖𝐄 𝐒𝐓𝐀𝐑𝐓 We begin with the small engagements a fixed-price sprint. After that you'll get a written architecture, a risk assessment, and an AI audit and roadmap you can take to your compliance team or board before committing further. Then we put one workflow live in your environment and prove it. Then we expand. You approve each milestone before it’s paid. 𝐖𝐇𝐀𝐓 𝐈 𝐁𝐔𝐈𝐋𝐃 AI automation and implementation. AI agents and agentic workflows wired into the systems you already run: your ledger, EHR, CRM and internal platforms. The automation sits inside the workflow, not beside it. I use n8n and GoHighLevel where they fit and build custom agents where they stop. Private and generative AI. Private and self-hosted LLM deployment on AWS Bedrock, Azure OpenAI or open-weight models. RAG and document intelligence over your own records, contracts and research, with the vector database inside your environment so nothing proprietary is embedded outside it. HIPAA-eligible services only, under a signed BAA. Machine learning. Predictive models trained and served inside your own environment, such as predictive maintenance and downtime reduction. EHR integration. Epic, Cerner, Athenahealth and Medplum through HL7 v2, FHIR and SMART on FHIR. Compliance and security architecture. IAM, private endpoints, audit logging and AI governance for PHI and other sensitive data. 𝐏𝐑𝐎𝐎𝐅 𝐘𝐎𝐔 𝐂𝐀𝐍 𝐓𝐑𝐘 𝐓𝐎𝐃𝐀𝐘 Sally is our own AI operating layer for COOs and leadership teams, and it has a live demo. It turns meetings into a decision log with owner, rationale and source. Its agents update Jira, move CRM deals and message channels, and sensitive steps stop for a human to approve. Every answer cites the document or meeting it came from, it reads from GoHighLevel and Odoo using your own logins, and it all runs inside your own cloud. It’s the same standard I bring to client work: AI that shows its work and acts only with permission. 𝐅𝐑𝐀𝐂𝐓𝐈𝐎𝐍𝐀𝐋 𝐂𝐓𝐎 𝐀𝐍𝐃 𝐀𝐈 𝐋𝐄𝐀𝐃𝐄𝐑𝐒𝐇𝐈𝐏 If you’re building this capability in house, I act as fractional CTO, head of AI or technical advisor. That covers your AI roadmap, architecture decisions, build versus buy, and who to hire. Three-month minimum. 𝐑𝐄𝐀𝐃𝐘 𝐖𝐇𝐄𝐍 𝐘𝐎𝐔 𝐀𝐑𝐄 Message me with the one AI project your compliance team is blocking, or the one process eating your team’s hours. I’ll reply with how I’d approach it, in plain English, before we talk scope or price. If it makes sense, we’ll book a 30-minute call this week. I take a small number of engagements at a time, so tell me what you’re facing and let’s get it moving.