THREE TRACKS. ONE STANDARD

Three tracks. Every one ends in production AI

Educate, Build, or Sustain - each track is designed for a different position on the AI maturity curve. The outcome is the same: AI that runs, is measurable, and is owned by your team

THE THREE TRACKS
Educate

For organisations that need to understand their AI position before they commit to building anything. This track delivers:

  • Structured assessment
  • Shared diagnostic language
  • A clear picture of where your AI stands
Build

For organisations that have a pilot, a stalled initiative, or a feature that needs to ship. This track delivers a system that is:

  • Working and deployed
  • Production-grade
  • Documented and handed over to your team
  • Free from vendor dependency
Sustain

For organisations whose AI is in production and needs to stay there. This track delivers:

  • Ongoing monitoring
  • Continuous optimisation
  • Rapid incident response

THE SERVICES
Educate

APMM Diagnostic Sprint

5–10 working days
How it works The APMM framework applied across five dimensions - adoption readiness, technical debt, data infrastructure, team capability, and governance posture - to produce an evidence-based maturity level and root cause diagnosis.
  • APMM Level Report: your organisation's current maturity level (0–4) with evidence-based justification
  • Gap Analysis: ranked gaps between current state and the next achievable level
  • Decision Brief: one page - what we found, recommended next step, and what inaction costs over the next 90 days
Start with a diagnosis
Educate

AI Readiness Workshop

Half-day or full-day session
How it works A facilitated APMM-grounded session that maps the team's AI landscape, surfaces the gap between current tool usage and production-ready deployment, and produces a shared working vocabulary for what "working AI" means in your organisation.
  • Workshop Findings Document: documented team AI landscape with gap map and priority ranking
  • APMM Self-Assessment Baseline: each participant's level scored against the five dimensions
  • Recommended Sequence: ordered next steps tied to your organisation's specific gaps
Book a workshop
Build

Pilot-to-Production Rescue

3–6 weeks
How it works Root cause diagnosis of the stalled pilot, followed by targeted remediation - rewriting only what failed, leaving what worked, and deploying to your production environment with defined uptime, error rate, and rollback criteria agreed before any code is written.
  • Deployed System: production-running AI system in your environment, not ours
  • Architecture Runbook: operational documentation your team can maintain without us
  • Handover Session: recorded walkthrough with your engineers, including model versioning and rollback procedure
Rescue the pilot
Build

AI Feature Sprint for SaaS

4–8 weeks
How it works Fixed-scope AI feature build against a production SLA agreed at the start - API cost modelled, latency benchmarked, hallucination handling defined, and integration tested against your existing stack before the sprint concludes.
  • Production-Ready Feature: integrated into your existing codebase, not delivered as a standalone module
  • Full Codebase in Your Repository: you own it completely at handover
  • Cost and Performance Baseline: documented inference cost, P95 latency, and error rate benchmarks from day one of production
Scope the build
Sustain

Monthly AI Ops Retainer

Ongoing
How it works Structured monthly operating rhythm - defined monitoring checkpoints, cost drift review, model performance tracking, and incident response SLA - applied to AI systems already in production, with findings documented in a monthly ops report your team owns.
  • Monthly AI Ops Report: performance, cost, and reliability summary against agreed production standards
  • Incident Log: documented root cause and resolution for any production failures during the month
  • Optimisation Recommendations: ranked, specific changes to improve cost or reliability in the next period
Discuss ongoing support

ENGAGEMENT PRINCIPLES
01

Paid from day one

There are no free pilots. The APMM Diagnostic Sprint is the entry point - because real diagnostic work takes time and expertise, and a paid engagement produces an honest one. You get a complete diagnosis regardless of whether anything follows.

02

Scope tight, deliver fast

Every engagement has a named deliverable list, a fixed timeline, and an end date agreed before work starts. Open-ended engagements are not offered because they are a structural invitation to expand scope without expanding value. If the problem is larger than the initial scope, we tell you - and scope a second engagement.

03

Human-in-the-loop always

AI augments your team's decisions. It does not replace professional judgment on consequential matters. Every system we build defines, before deployment, where human override sits - and that boundary is non-negotiable regardless of how confident the model appears.

04

Transfer knowledge, not dependency

We train your team to sustain what we build. Every engagement concludes with a handover session, documented architecture, and a runbook. The engagement relationship continues because it is valuable - not because leaving would be painful or technically impossible.

05

Document everything

Every engagement produces artefacts your organisation owns completely. Architecture documentation. Runbooks. Decision logs. If the engagement ends tomorrow, your team has everything they need to continue. That is not a contingency - it is the design.


THE PRODUCTION STANDARD

What "production-grade" means at Devverse Labs - defined before any build begins, measured after every deployment.

Standard Definition In Practice
Reliability >95% uptime minimum, agreed before build Monitored post-deployment. Not a marketing claim - a contractual baseline. If we cannot define and measure it for a given system, we say so before the engagement starts.
Observability Error rate defined per system. Cost per run budgeted. P95 latency agreed before architecture decisions. Every production system has monitoring in place at handover. You can see what the AI is doing, what it costs, and where it fails - without asking us.
Handover Rollback capability required on every system Your team receives the full codebase, the architecture documentation, model versioning, and a defined fallback procedure. You do not rent AI from us. You own it.

FREQUENTLY ASKED
Why fixed-duration engagements? Can't we start with a retainer?

Fixed engagements exist to protect both sides. A retainer from day one creates the wrong incentive structure - the work expands to fill the time rather than the scope driving the timeline. Fixed duration with named deliverables means the engagement ends when we've delivered what we said we would deliver. Once a production system is running and your team is trained to maintain it, the retainer conversation makes sense. Not before.

Can you work with our existing AI vendors and tools?

In most cases, yes. The APMM diagnostic maps your current stack - existing models, APIs, and tooling - and the remediation or build work takes place within it wherever possible. We do not require you to migrate to a specific vendor stack. Where a tool is genuinely the source of the problem, we say so explicitly in the diagnostic, with evidence, before recommending any replacement.

What if the diagnostic reveals a problem you can't fix?

We tell you. The diagnostic report will name the problem, explain why it falls outside our scope or capability, and recommend who should handle it. This happens rarely, but it happens - particularly in regulated industries where data handling constraints limit what is technically addressable. If the honest answer is "this needs a different specialist," you get that answer from a complete diagnostic, which is still a better outcome than another quarter of informed speculation.

What exactly is included in the handover?

Full codebase in your repository. Architecture documentation your team can maintain. A runbook for operational issues. Model versioning and rollback procedure. Usage and cost monitoring configured and handed over. A recorded handover session with your engineers. These are not conditional on scope or price tier - they are included in every Build engagement.

AI that runs. Or an honest explanation of why it doesn't

Book the Diagnostic Call

30 minutes · Written follow-up within 24 hours · No pitch