NeoMonarch.
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Product studio · AI engineering consultancy

Enterprise platforms, built at AI speed. Proven on every change.

We design, build and run platforms for commerce, logistics, financial services, insurance and health. Senior engineers direct AI virtual engineers, and a regression harness checks every commit.

  1. $ bridge run reorder --autonomy=approve
  2. plan 4 steps · budget $5,000
  3. call inventory.check(sku=OM-1L)
  4. call pricing.quote(qty=40)
  5. policy within spend limit
  6. approval waiting on buyer…
  7. eval 0.97 · regression gate passed
  8. ledger v3 sealed 10:42:07Z

Platforms that run the business, end to end.

All platforms

Commerce 360

Conversational and omnichannel commerce — storefront, chat, voice ordering, an order desk and agent-ready APIs for buyers’ AI.

  • 3,350+ automated Java tests
  • MCP + UCP endpoints
  • BYO-LLM gateway
Explore Commerce 360
A shopper paying at a store counter with a smartphone

Gangway

Bring new business customers aboard in days, not weeks: AI agents collect and verify their documents, explain the contract in plain language, and keep every version on a tamper-evident record both sides can check.

Explore Gangway

InsightPro

Ask your data in plain language. Natural-language analytics, dashboards and voice-of-customer in one workspace.

Explore InsightPro

One AI stack, governed end to end.

Explore the stack

Retrieval, generative AI, statistical machine learning and agent workflows, run by one orchestrator that acts on its own inside the limits you set, and proves every step.

The model is the engine. The harness is the engineering.

How we build
  1. Frame

    Founder and client agree the outcome, the constraints and what “done” means.

  2. Specify

    Requirements become machine-readable specs and acceptance tests.

  3. Build

    AI virtual engineers work in parallel lanes, reviewed by a senior engineer.

  4. Prove

    Regression harness, security scans and performance checks gate each change.

  5. Ship & run

    Deploy to your cloud with monitoring, then keep improving it.

How we build, in depth

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