Case Study - AI platform for regulated manufacturing leaders

Challenge

Murmuratto targets engineering leaders in regulated manufacturing — environments where compliance gaps, downtime, and lost frontline insights directly hit margins. The product had to complement existing ERPs and SOPs, not replace them, while adding AI that leaders would actually trust.

That meant multi-tenant SSO, executive dashboards, secure document handling, and AI features that produce traceable, decision-ready output — not black-box summaries.

Approach

I built the front end with Remix, React, and TypeScript for SSR and fast data hydration with TanStack Query. Executive dashboards use ECharts for financial, time, and waste savings metrics.

On the backend, I integrated Parse Server with MongoDB and Redis, wired Azure AD for SSO, and enforced permissions with JWT and CASL. AI capabilities run through AWS Bedrock, Polly, and Transcribe, with semantic duplicate detection via Pinecone embeddings. Supporting Python agents on FastAPI handle specialized pipelines, and file uploads pass through ClamAV scanning before landing in S3.

Monitoring runs through Sentry, with E2E coverage via Katalon and deployments through Docker and CI/CD.

Results

• Executive dashboards giving leadership real-time visibility into operational and financial metrics
• AI-powered voice transcription and executive summaries integrated into existing improvement workflows
• Semantic duplicate detection reducing manual review across large document sets
• Secure upload pipeline with malware scanning and cloud storage
• Platform positioned for regulated manufacturing with SOC 2 Type II compliance (per Murmuratto public materials)

Context from the product

Murmuratto publicly highlights pilots starting at $25K, usage across life sciences manufacturing sites, and measurable value capture from frontline improvements — the engineering work above supports those product promises in production.