AI systems that ship to production. Not decks that don't.
Fixed-scope entry offers plus a 90-day operating partner path. Published pricing. The practitioner who scopes it builds it -- no hand-offs, no junior surprises.
Solutions
Start with a tight sprint or audit. Continue only when the backlog justifies retained execution. Each path is scoped, priced, and delivered by a senior practitioner.
AI Stack Audit
Scored assessment across 5 dimensions. Clear verdict. 90-day roadmap.
2 weeks
$15,000 fixed
- Know in 2 weeks if your data can hold production AI -- with a scored 5-dimension readiness assessment
- A prioritized fix list with scored gaps -- not a consultant's slide deck
- A 90-day implementation roadmap with cost estimates your board can approve
- Clear signal: which AI use cases to build now vs. drop (with a use-case prioritization matrix)
- Board-ready executive summary you present with confidence
RapidOps
From manual to automated in days. One workflow, one sprint, working code.
1-2 weeks
$5,000-$8,000
- By end of week 2: one workflow runs without anyone touching it
- Handles the logic Zapier and Make can't -- multi-step, conditional, production-grade
- Deployed with a runbook your team can maintain without calling us
- 2 weeks of post-delivery support included
Data and AI Operating Partner
90 days of retained execution after the first sprint, audit, or scoped build proves the backlog is real.
3-month minimum
Scoped on the fit call
- One senior technical owner for the next data, workflow, or AI build lane
- Weekly priority review with the business owner so the backlog stays sequenced
- Workflow stabilization, data foundation repair, reporting automation, or first production AI build
- Written handoff as work ships so your team is not dependent on a consultant forever
DataCore
dbt + Terraform + CI/CD. The data layer everything else depends on.
4-8 weeks
Scoped per engagement
- A data foundation AI agents can run on -- dbt-tested data models
- Terraform-managed cloud infrastructure you can provision, tear down, and trust
- Automated quality gates and CI/CD pipelines that catch bad data before production
- Docs written for your next hire, not just for you today
AgentForge
Production-grade AI agents. Built on trusted data, not demos.
4-12 weeks
Scoped per engagement
- An AI agent in production -- architecture designed, not just a proof of concept
- Production deployment with monitoring -- observable from day one
- Reliability-tested so it fails gracefully, not silently
- Your team can operate it without us on call (handoff runbooks included)
How engagements progress
Most clients start with a diagnostic or a single sprint. Retained execution starts only after the first proof point shows a real backlog.
Assess
AI Stack Audit or a free 30-minute discovery call. Understand where you stand.
Quick Win
RapidOps sprint. Automate one workflow. See results in days, not months.
Operate
Data and AI Operating Partner. Keep one senior owner on the backlog for 90 days when the first proof point exposes more work.
Foundation
DataCore build. The data infrastructure that makes AI agents reliable and maintainable.
Scale
AgentForge deployment. Production AI agents built on the foundation you now trust.
Why MLDeep publishes pricing
Hiding pricing wastes everyone's time
Most AI consultancies make you "schedule a call" before learning what anything costs. You shouldn't need a sales pitch to know if a service fits your budget.
Fixed scope prevents scope creep
Fixed-price entry offers and clearly priced retained execution make scope obvious. You know what begins as a sprint, what becomes a 90-day build lane, and what should stay out of scope.
The team that quotes is the team that delivers
No sales team, no partner-to-analyst handoff. We scope the project, price it, and deliver it. The price reflects a direct senior assessment of the work.
Technology partnerships
Stack-agnostic delivery. The architecture fits your stage and your data, not a preferred vendor.
Ready to start?
Book a free 30-minute discovery call. No pitch deck. Just a straight conversation about what you need and whether MLDeep is the right fit.