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manufaujdar/README.md
A constellation connecting healthcare, trustworthy AI, research, and creative systems Portfolio status across trustworthy AI, clinical interfaces, translational research, and creative systems

Manu Faujdar

Healthtech builder · Trustworthy AI researcher · Clinical workflow designer

Master LLM · AI Gateway · Smart Glasses · LinkedIn


TRUST
privacy · safety · evaluation

CLINICAL
workflow · devices · care

RESEARCH
evidence · validation · translation

CREATE
products · media · interfaces

I build systems that make complex technology more observable, safe, and useful—from AI routing and privacy controls to clinical devices, translational research tools, and creative AI products.

Selected public work

◈ AI Routing Gateway

Explainable model and tool routing with deterministic decisions, specialist-agent workflows, and explicit safety boundaries.

Explore repository →

⌁ Smart Glasses

Vendor-neutral healthcare smart-glasses research with capability contracts, simulators, safe-stop behavior, and workflow experiments.

Explore repository →

More public projects

AI Firewall
Fail-closed sensitive-data inspection for outbound AI calls.

SystemBench
Reproducible evaluation for complete AI systems.

Reflection AI
Consent-aware personalization and memory framework.

SignalForge
Content intelligence and evaluation dashboard prototype.

VideoViber
Agentic, spec-driven video creation workspace.

Prompt Enhancer
FastAPI service for improving text prompts.

Engineering focus

clinical workflow · intended use · privacy controls · explainable routing · failure modes · validation planning · synthetic testing

I turn ambiguous health-technology problems into bounded systems: define the user and non-use case, map risks, make decisions observable, test failure paths, and document what the evidence does—and does not—support.

◈ Trustworthy AI

  • allow / redact / block controls
  • metadata-only audit events
  • explainable model and tool routing
  • explicit human authorization gates

⌁ Clinical prototypes

  • vendor-neutral capability contracts
  • disconnect and safe-stop behavior
  • privacy boundaries
  • synthetic, offline-testable workflows

◌ Validation

  • evidence mapping
  • intended-use definition
  • confounder and provenance planning
  • repeat-trial evaluation

✦ Delivery

  • needs framing
  • prototype requirements
  • implementation-risk mapping
  • clinical / product / data / engineering coordination

The wider portfolio

AI safety · model evaluation · clinical workflow · smart devices · biomarkers · digital health · creative AI

The public repositories are the visible edge of a larger portfolio of private product labs and research systems. Private work is intentionally represented as a visual category rather than linked before it has a safe public release, complete documentation, and a reproducible demo.

Evidence boundary: clinical projects shown here are research-stage or synthetic/non-clinical unless explicitly stated in the repository.

Working principles

◈ Observable ⌁ Bounded ◌ Resilient ✦ Memorable
Make decisions inspectable Make evidence and non-use explicit Design for graceful failure Give complex systems a human interface

Now

Turning separate experiments into coherent public flagships with reproducible demos, explicit safety boundaries, and evidence-aware engineering.

Popular repositories Loading

  1. Prompt-Enhancer Prompt-Enhancer Public

    Framework to evaluate, enhance, and optimize prompts before LLM API calls

    Python

  2. VideoViber VideoViber Public

    AI-assisted video vibe generation and editing workspace

    TypeScript

  3. ai-routing-gateway ai-routing-gateway Public

    Explainable AI routing gateway that sends each request to a suitable model or specialist workflow.

    Python

  4. systembench systembench Public

    End-to-end AI system evaluation framework for routing, tools, provenance, safety, latency, operability, and task success.

    Python

  5. ai-firewall ai-firewall Public

    Local-first AI firewall that inspects outbound data and allows, redacts, or blocks sensitive information before cloud AI calls.

    Python

  6. smart-glasses smart-glasses Public

    Research platform for simulating clinical smart-glasses workflows, device contracts, capture, voice, and safe-stop states.

    Python