AI in production, guaranteed.
Your demo impressed the board. We ship the version that survives security review, compliance, and real traffic - on your infrastructure. You own the code.
The demo works. Production doesn’t. We fix that.
A demo proves the model can do it once. Production means it holds up every time - under security review, in front of auditors, at real traffic, on real budgets. Here is what actually kills enterprise AI projects:
- ✕ Security finds prompt injection. The project stalls for six months.
- ✕ Compliance asks "where does the data go?" Nobody has an answer.
- ✕ The chatbot cites documents the user should not see. One incident, project dead.
- ✕ Token costs 4x overnight. Finance pulls the plug.
- ✕ Nobody owns it after launch. It degrades quietly until someone turns it off.
None of these are model problems. They are engineering, security, and operations problems. That is what we do.
Get your production roadmap →Not an agency. Not a dev shop. The partner for AI that has to pass audit.
AI agencies sell demos. Dev shops sell hours. SaaS copilots sell someone else's roadmap. Metaheuristic is built for one job: taking AI systems through security review, compliance, and go-live - on your infrastructure - and keeping them running.
On-prem and air-gapped deployment. Your data never leaves your perimeter. The answer to "where does the data go?" is nowhere.
Permission-aware RAG, full audit logs, EU AI Act documentation. Your auditors get artifacts, not promises.
You own the code, the prompts, the evals, the IP. Fire us any time and everything keeps running. No lock-in is the guarantee.
Start small. Prove value. Scale with a guarantee.
For teams with a stalled PoC, an AI mandate and no plan, or a "do something with AI" directive from the board.
- · Workflow + data readiness audit
- · ROI-ranked use-case map
- · Target architecture blueprint
- · Security + compliance pre-check
- · Board-ready business case
- + Eval-suite starter kit
- + Model shortlist with cost projections
- + 90-day quick-wins list
If you would not confidently take the roadmap to your board, we credit 100% of the fee toward any future engagement - or refund it. Your call.
- · Hardened inference, routing, failover
- · Guardrails + human approvals
- · Golden-set evals gated in CI
- · OWASP LLM red-team before go-live
- · Monitoring, cost control, audit logs
- · Runbooks + full handoff
- · Permission-aware RAG + agentic workflows
- · CRM, ERP, tickets, APIs, documents
- · Guardrails, evals, audit logs from day one
- · Weekly shipped milestones
- · You own code, prompts, evals, IP
- · Air-gapped serving, zero external data flow
- · Multiple systems, one governance frame
- · Fractional AI CTO + board reporting
- · AgentOps retainer with response SLAs
- · Compliance artifacts kept current
Every engagement: fixed scope, fixed milestones, you own the code. The Discovery Sprint fee is always credited toward your build.
We take the risk so you don't have to.
Enterprise AI is risky enough. Your engagement with us shouldn't be. Four guarantees, in writing, on every contract:
Your Discovery Sprint delivers a production roadmap you would take to the board - or we credit or refund the fee. Your call.
Nothing ships until it passes its eval suite and OWASP LLM security review. If it doesn't pass, we fix it at no additional cost.
Code, prompts, evals, IP - yours from day one, with a documented exit path. If we disappeared tomorrow, your systems keep running.
Fixed scope, fixed milestones. If a milestone slips because of us, the next one is free.
We can offer these because of how we build: evals before features, security before launch, documentation before handoff. The guarantees aren't marketing - they're the process.
Start risk-free →Things other firms bill for. We just include them.
Bonus stack confirmed for engagements booked this quarter. Scope and inclusions are reviewed quarterly as demand grows.
Everyone sells "AI." Here's what you actually get.
| At a glance | Metaheuristic | In-house hire | Generic dev shop | No-code (Zapier/Make) | Off-the-shelf copilot | DIY ChatGPT |
|---|---|---|---|---|---|---|
| What you get | Production system, guaranteed | Capacity, eventually | A build, maybe | Brittle automations | Someone else's roadmap | A prototype |
| Time to production | 2–10 weeks | 6–12 months, hire first | Months, then handoff | Days, then stuck | Instant, and generic | Never quite |
| Passes security review | Red-teamed, OWASP LLM Top 10 | Depends who you hire | Rarely attempted | - | Black box | - |
| Sovereign / on-prem | Air-gapped, by default | Possible | Rarely | - | Vendor cloud only | - |
| Data permissions | Permission-aware RAG, built in | Depends | - | - | Vendor-defined | - |
| Audit trail | Immutable, replayable logs | Depends | - | - | Partial | - |
| Cost control | Routing + caching (−71% typical) | Ad hoc | Ad hoc | Per-task fees | Per seat, forever | Unmanaged |
| Ownership | Your code + IP, contractually | Yours | Negotiated | Locked-in | Vendor | Yours |
| After launch | AgentOps retainer + SLAs | On the team | Goodbye at handoff | You maintain | Vendor SLA | You maintain |
| Risk if it fails | Our guarantees absorb it | Yours | Yours | Yours | Switching cost | Yours |
A demo proves the model can do it once. We build the guardrails, evals, security, and ops that make it hold up every time - and we stay on to run it.
Get the system, not the demo →route(task) {
if (simple) → haiku
if (reason) → sonnet
if (critical) → opus
if (cached) → return hit
}· cost
Audit in. System out.
We map workflows and data readiness, then rank every opportunity by ROI and risk. You get a defensible answer to "why this use case first."
Architecture plan plus a working prototype before the production build. Proof, not promises, before the big spend.
Permission-aware RAG or agentic workflows with guardrails and integrations. Working software every week, never a black box.
Golden-set evals and an OWASP LLM red-team gate the release. Evidence for security and compliance sign-off.
Human approvals, safety limits, and immutable audit logs. Ownership transfers to you. Go-live your auditors approve of.
Monitoring, evals, version management, routing, and cost control under SLA. AI that still works - and is still on budget - in month 18.
An agent that asks before it acts.
This is the difference between a demo and a system. Watch what happens when an agent touches real money:
user› "Customer #2841 was double-charged. Fix it." retrieve› permission-aware RAG · 3 sources - orders/2841.json allow ✓ - policy/refunds.md allow ✓ - finance/ledger.xlsx deny ✕ (out of scope) reason› duplicate charge confirmed · within policy tool› stripe.refunds.create({ amount: 480_00 }) ⏸ guardrail: refund > $200 needs human approval ✓ approved by jordan@acme · 41s › refund issued · customer notified · logged $ ▍
{ "action": "refund",
"amount": 48000,
"approved_by": "jordan",
"sources": 2,
"status": "completed" }Every retrieval permission-checked. Every action guardrailed. Every step logged, signed, and replayable. This is what "production-ready" actually means - and it's what your security team will ask for.
Before and after, in numbers.
Caching + model routing. Same quality, same latency, a third of the spend.
Fixed scope and milestones, with evals and a security review gating every release.
Yours from day one, contractually. If we disappeared tomorrow, your systems keep running.
Your competitors are stuck in PoC purgatory. You don't have to be.
One Discovery Sprint. 2–4 weeks. You walk away with a board-ready roadmap, an architecture blueprint, and a security pre-check - guaranteed, or the fee comes back. The fee credits toward your build. The only risk is staying stuck.