Is this your level?

Level 3 is the right fit when standard AI tools aren't precise enough for your domain.

You need AI to produce decisions you can defend, not just drafts
Your data is complex, structured, and operationally critical
You need source-grounded outputs with full audit trails
Off-the-shelf tools can't handle your domain specificity

What it costs

Five tiers from architecture scoping through to large-scale multi-source builds.

Start here: no commitment to build
Discovery & Architecture · $500–$1,250

Scope your intelligence layer before any build begins. Architecture, data mapping, and a clear delivery plan, all in one week.

$3,500–$5,500
6–8 weeks
Small Intelligence Layer

Single-domain intelligence system with source grounding, review queue, and API delivery.

Most common
$5,500–$8,500
8–10 weeks
Standard Bespoke Build

Full bespoke intelligence layer with audit trail, confidence scoring, and structured output delivery.

$8,500–$12,000
10–12 weeks
Strong Intelligence System

Multi-source intelligence with role-based outputs, exception scoring, and decision logging.

$12,000–$18,000+
12+ weeks
Large Multi-Source Build

Cross-system intelligence with dashboard, multi-workflow agents, and governance layer.

Retainer options

Intelligence systems need ongoing optimisation. Retainers keep your layer performing as data and requirements evolve.

$1,000–$1,500/mo
Intelligence maintenance

Monitoring, schema updates, QA, light improvements.

$1,500–$2,500/mo
Managed intelligence operations

Cost review, dashboard improvements, workflow expansion.

$2,500–$3,500/mo
Multi-workflow intelligence support

Multiple systems, regular optimization, governance review.

What you get

A custom-built intelligence layer that produces auditable outputs, not just a smarter chatbot.

1Schema packs & source grounding for your data
2Custom-trained or fine-tuned intelligence layer
3Review queues, confidence scoring, and audit trail
4API/webhook delivery to your existing systems
5Exception routing and escalation logic
6Ongoing performance monitoring and retraining cadence

What this is not

Level 3 requires architecture, data mapping, schema design, and auditability. If your use case doesn't need these, Level 2 is the right fit.

Claude Project with uploaded files
Custom prompts or content repurposing workflows
Simple document summaries or inbox assistants
Single Zapier or n8n automation
Chatbot with a knowledge base
Workflow agents without auditability or source tracing

What we build

Domain-specific intelligence systems wired into your existing stack.

Predictive Maintenance Intelligence

AI that reads sensor data, maintenance logs, and supplier lead times to predict failures before they happen, and schedule interventions automatically.

Exception Control Tower

An intelligence layer that monitors your operations in real time, flags exceptions, scores severity, and routes the right action to the right person.

Document Intelligence Layer

Contracts, reports, and compliance documents processed into structured, source-grounded intelligence with full audit trails, not just summaries.

AI Quoting & Pricing Engine

Margin-aware quotes generated instantly from lane data, carrier rates, and historical win/loss patterns, with explainable pricing logic.

Portfolio Risk Intelligence

Live intelligence across a property or asset portfolio: vacancy risk, maintenance flags, pricing anomalies, and market signals in one governed view.

QA & Review Intelligence

AI-generated outputs reviewed, scored, and approved through a structured QA layer, with confidence scoring and escalation routing.

Level 3 in practice

Level 3ManufacturingRaypack

Turning production volatility into predictable, lower-waste output

Predictive scheduling and in-line quality-control AI that dynamically adjusts production runs from live demand signals, deployed in 12 weeks, ROI well ahead of the 12-month payback target.

42-48%
ROI
+35%
Forecast Accuracy
-40%
Material Waste
-28%
Rework

When you're ready to move up

These signals mean it's time to look at Level 4.

You're running multiple AI deployments that need unified governance
You want AI as infrastructure, not a collection of isolated systems
Cost, compliance, and auditability are non-negotiable at scale
You're ready to make AI a permanent part of your operating model

Step back

Level 2: Workflow Implementation

Automate and govern your highest-value workflows first.

When you're ready

Level 4: AI-Native Infrastructure

AI as your operating model, governed, observable, and compounding margin.