AI-era software · mid-market & enterprise consulting

Make your software work for AI agents — before your competitors do

We help mid-market and enterprise teams ship AI-ready software, retrofit legacy systems with MCP layers, and redesign processes for autonomous agents. Real engineering, not slide-deck strategy.

  • 12-week typical engagement
  • Built on AWS, Anthropic & Vercel
  • Operating across 5 markets

Built on the stack your team trusts

  • AWS
  • Anthropic Claude
  • Sanity
  • Vercel
The problem

Your software wasn't built for AI agents

Most enterprise systems were designed before AI agents existed. They can't be read, operated, or automated by autonomous agents — leaving your team doing work that machines should handle, and your AI investments stuck in pilot mode.

The solution

Make every system agent-ready

Agent-ready software exposes an MCP layer that lets AI agents connect to your systems, understand your data, and take action — without breaking what already works. We design, build, and integrate that layer.

Process as proof

How we ship — and why it works for mid-market and enterprise

12 wk

Typical first engagement

From kickoff to a working MCP layer integrated with at least one production system.

5

Markets we operate in

United States, Canada, United Kingdom, Chile, and remote enterprise engagements globally.

0

Slide-deck strategy decks

Every engagement ships working code. We charge for outcomes, not PowerPoints.

100%

Production-shipped MCPs

Every MCP layer we deploy reaches production, not a sandbox.

How we work

From discovery to autonomous workflows in 12 weeks

We move fast, but never on faith. Each phase has measurable exit criteria — you know what you're getting before we move forward.

  1. 01

    Discovery & AI-readiness audit

    Week 1–2

    We map your stack, processes, and data. You get a written audit of what's agent-ready, what isn't, and the highest-leverage automations to ship first.

  2. 02

    MCP architecture & build

    Week 3–8

    We design and build the MCP layer your agents need — production-ready, with auth, observability, and version control. No throwaway prototypes.

  3. 03

    Integration & validation

    Week 9–11

    We integrate with Claude, ChatGPT, or your custom agent. We validate end-to-end with your real workflows, not synthetic tests.

  4. 04

    Handoff & ongoing partnership

    Week 12+

    Your team ships next. We document, train, and stay on retainer as you expand the agent surface across more processes.

Mid-market companies don't need another AI strategy deck — they need software that AI can actually operate. That's the gap we close, in code, on production timelines.
Lorena Campos, Director, Humind Labs AI

Lorena Campos

Director, Humind Labs AI

Frequently asked

What teams ask before working with us

We don't run workshops. Every engagement ships working code in production. The discovery audit is 1–2 weeks; everything after that is build, integrate, and validate. If you want a strategy deck, we'll point you elsewhere.

Yes. Most of our work is integrating MCP layers into existing AI initiatives that have stalled because the underlying software can't be operated by agents. We work alongside your existing AI team, vendors, and stack.

Our first engagement is typically a 12-week build that starts in the low-six-figures USD, scoped against your specific systems and outcomes. We're transparent about pricing on the discovery call — no surprise quotes.

Occasionally — when the use case is high-leverage and the team has the technical maturity to absorb production AI infrastructure. Most of our work is with 50–500 mid-market companies and 500+ enterprises where the integration scope justifies a dedicated engagement.

Anthropic Claude (including the MCP standard), AWS Bedrock, and custom agentic frameworks. On the software side: AWS, Vercel, Next.js, Python/Node services, common databases. We adapt to your stack rather than imposing ours.

Free download

The AI Readiness Checklist

A 1-page diagnostic mid-market and enterprise teams use to identify which systems are agent-ready, which aren't, and where the highest-leverage AI automations live in your business.

  • 12-question diagnostic across data, processes, and tooling
  • Scoring rubric you can run in a 30-minute meeting
  • Used by ops leaders before scoping AI engagements

Ready to make your software AI-operable?

Tell us your most painful manual process. We'll show you what an agent-ready version looks like — and how long it would take to ship.

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