Enterprise AI fails in production for three reasons: untrusted outputs, runaway token costs and integrations that break at scale. I design the systems that solve all three, and I stay until they run on their own. Where AI stops being a feature and becomes a system: that is where I work.

I move companies off brittle LLM wrappers and onto production-grade AI systems: agentic workflows and multi-agent orchestration, advanced RAG with context engineering, low-latency voice, and under them the eval harnesses, programmatic guardrails, LLMOps and token economics that keep them standing once real users arrive. The part I care about is the part after the first result: the agent that still has to answer well with a tool down, in a language the evals never covered, under a budget. Right now that work is at TWINii, where we build real-time AI twins of real experts, and with a small number of seed to Series B teams I join part-time, embedded.

Lately, I've been working on

• Real-time voice agents: latency budgets, interruption handling, memory that survives a session, guardrails that survive a user.
• Multi-agent orchestration and MCP tool layers that hold their shape as the number of tools grows.
• Eval harnesses and release gates, so a model or prompt change ships with evidence rather than hope.
• Spec-driven development with AI-assisted engineering standards, so coding agents write inside boundaries the team agreed on first.
• Security and supply-chain hardening across an organisation. That programme is why polinrider-cleaner exists.
• Inference cost. I read the token bill the way I used to read the AWS bill.

Some of what I've built

• TWINii: the real-time voice pipeline behind AI twins of experts, who answer in their own voice.
• Devnagri AI: the voice and language AI platform across 22 Indian languages, as Solutions Architect and then Fractional CTO: multilingual AI workflows, LLMOps and a hybrid cloud that kept spend down while load went up.
• Shiprocket: the core of its omnichannel commerce integrations. The company is now a unicorn.
• HumanFirewall: first product live in 45 days, as Acting CTO.
• Balluun: five years as Solutions Architect for a Silicon Valley B2B market network, through its cloud-native migration.

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_{Mandeep Singh  ·  Delhi, India  ·  msingh.com  ·  the strips update daily from scripts/}