Named programs with before/after metrics — cycle time, uptime, and cost.
Use this page to brief a hiring committee or a consulting buyer in one pass.
How an EU-regulated lending fintech deployed a conformity assessment blueprint to comply with EU AI Act Annex III high-risk lending mandates before.
Client: Anonymized EU-Regulated Lending Fintech
How a global B2B SaaS marketplace platform deployed a governed Model Context Protocol (MCP) Gateway to scale AI agent tool integrations securely.
Client: Anonymized Global B2B SaaS Platform
How a multi-hospital regional health system deployed a 4-agent HIPAA CrewAI architecture, FHIR R4 interoperability, and Amazon Bedrock to cut prior authorization turnaround from 9 days to 38 seconds.
Client: Multi-Hospital Regional Integrated Delivery Network (IDN)
How a leading commercial bank deployed specialized AI agents for code review, automated compliance gating, and canary rollbacks to cut deploy cycles to…
Client: Tier-1 Multinational Commercial Bank (Latin America)
enterprise MCP integration — A global logistics enterprise connected SAP ERP, WMS, and ITSM to governed AI agents using outbound-only MCP tunnels.
Client: Global Logistics Enterprise
How a mid-market CPG manufacturer deployed autonomous SCM planning agents integrating NetSuite ERP data with Shopify POS streams to reduce stockouts by 30%
Client: Mid-Market CPG Manufacturer
SOC 2 Type II for an AI-Native SaaS: Passing the Auditor's AI Questions in One Cycle By Vatsal Shah · 2026-06-14 · Compliance / Business Technology For.
CRM Transformation B2B SaaS 2026 — CRM Transformation - How a B2B SaaS Vendor Compressed Lead-to-Cash Cycle by 41% with Agentic Workflows
Proof-of-Impact - How a Mid-Market Manufacturer Retired 16 AI Pilots and Scaled 4 Agents to P&L Expert analysis and implementation guidance by Vatsal Sh
Agent Governance Global Insurer 2026 — Agent Governance - How a Global Insurer Built a Registry and Cut Shadow AI Incidents by 78%
ITSM Domain Shift: How an Enterprise MSP Cut MTTR by 52% with Governed Service Agents By Vatsal Shah · 2026-05-27 · IT Operations Modernization For.
agentic zero trust — How a global fintech secured 5,000 autonomous agents using the Agentic Trust Framework (ATF), MCP tool-gating, and identity-first s
self-healing supply chain autonomous ERP — How a global manufacturing leader transitioned from a static legacy ERP system of record to a composable, aut
ambient clinical documentation copilots — How a major hospital network integrated ambient AI scribes and clinical decision support into their EHR, reduc
Financial Services Tier2 Bank 2026 — Financial Services - How a Tier-2 Bank Reduced Fraud False Positives by 95% Using Machine Learning Anomaly Detection
Omnichannel Retail CDP Integration 2026 — Omnichannel Retail & CDP Integration - Unifying 2 Million Customer Profiles in 90 Days
Healthcare Operations - How a Regional Hospital Cut Nurse Overtime by 35% Using Automated Resource Allocation Expert analysis and implementation guidanc
How a top-tier FinTech transitioned from rules-based detection to adaptive behavioral biometrics, achieving 99.9% detection accuracy against synthetic…
Manufacturing ERP Modernization - How Predictive Maintenance Saved a $120M Automotive Plant Expert analysis and implementation guidance by Vatsal Shah f
Array 2026 — Array Expert analysis and implementation guidance by Vatsal Shah for enterprise teams in 2026.
The Problem: The Hallucination Ceiling Most enterprise AI projects hit a "80% plateau"—where the model is impressive in demos but fails to reach the 99%.
The Problem: The "RAG Ceiling" and Support Fatigue Our client sat at the center of a massive logistical web.
The Problem: The Hallucination Horizon of Vector Search When our team audited the client's existing generative AI pipeline, it was built on standard.
The Problem: The "Maintenance Trap" Legacy code doesn't just sit there; it rots.
The Problem: The Latency Wall A "demo-grade" LLM application typically uses a direct API call to a provider.
The Problem: The "PoC Cemetery" & Cost Sprawl Most enterprise AI initiatives die in the "PoC Cemetery"—the gap between a working Jupyter Notebook and a.
Client / Problem Overview Our client, a high-growth automation enterprise, was struggling with a massive bottleneck in their legal and compliance document.
Client / Problem Overview - Industry: Financial Services & Global Banking - Scale: 85,000+ Employees globally - Business Challenge: The client.
The Problem: Intelligence vs. Compliance For financial institutions, "intelligence" is useless if it exposes sensitive customer data.
Enterprise AI platforms, agentic workflows, solution architecture reviews, legacy modernization and software or application delivery. Selected work with context, constraints and outcomes is on https://shahvatsal.com/work and in the case studies, so a buyer can check fit before a call.
Three models: a fixed-scope architecture review, advisory or consulting, and delivery leadership for a software project. Fixed-price, time-and-materials and dedicated-team contracts have all been used. Scope and deliverables are agreed in writing before work starts.
A fixed-scope, 2-hour executive deep dive on agentic AI readiness, platform topology and governance gaps, followed by a written executive brief with an architecture decision record pack and a prioritized 90-day roadmap. Request it from the contact page.
Yes. Case studies on this site describe the problem, architecture, rollout and measured outcome. Delivery figures from the current role, such as 98% on-time delivery and 100% client satisfaction, are self-reported, so ask for references or supporting reports on a discovery call.
Mobile and app stacks (Android, Flutter, Java, Ionic, Angular, React Native), backend and automation (Firebase, Supabase, n8n, Make.com), cloud (AWS, Google Cloud, Azure) and AI tooling (OpenAI, Anthropic, Google Gemini, LangChain). The full list is on https://shahvatsal.com/skills.
Send a short brief through https://shahvatsal.com/contact with the focus that fits, or book a 30-minute executive briefing. Expect a reply within 24 to 48 hours. A first call covers goals, constraints and whether an architecture review or a delivery engagement fits better.
