ZZ Solutions
Services/$60,000 – $120,000

Full AI Integration Platform

Multiple workflows automated. One AI-connected intelligence layer. The whole team benefits.

This is for organizations that are done with incremental improvements and want to transform how they operate. Not one automation — a platform. Multiple workflows running autonomously, a shared AI intelligence layer that connects your data across systems, and assistants deployed across your teams. We've done this before. It's not a research project.

$60,000 – $120,000
5–8 months
What's included

Everything in this engagement

A Full AI Integration Platform engagement spans 5–8 months and covers everything from architecture to launch: multiple automated workflows, a centralized data and AI layer, cross-team assistants, and the documentation and training your team needs to extend it themselves. We work in parallel workstreams so you see results throughout the engagement, not just at the end.

→Fixed price — you know the total cost before we start
→Parallel workstreams mean you see results throughout, not just at month 5
→Platform is designed to be extended by your own team after handoff
→30-day post-launch support is included, not an add-on
1
Multi-workflow automation architecture
Full system design covering all automation workstreams — agent responsibilities, integration points, shared infrastructure, and governance model.
2
Centralized AI intelligence layer
A shared data layer that connects your systems and gives every AI component access to the same grounded, real-time business context.
3
Automated workflows — built and deployed
Each workflow built, integrated, tested, and deployed independently. Parallel workstreams mean earlier delivery.
4
AI assistants across business units
Team-specific assistants deployed into the tools each group uses, tuned to their actual workflows and data.
5
Monitoring, alerting, and audit infrastructure
Full observability from day one. Every automated decision is logged, anomalies are alerted, and dashboards make system health visible.
6
Documentation, training, and 30-day post-launch support
Your team learns to operate and extend the platform. We stay engaged for 30 days after launch to resolve issues and tune performance.
Architecture

How we keep the work production-ready

Each service is scoped around the same core standard: the AI must be grounded, measurable, observable, and safe to operate. The output is not a prototype that only works in a demo. It is a system your team can trust, inspect, and improve.

Principle 01

Data first

Identify the source of truth before designing the AI behavior.

Principle 02

Controlled autonomy

Let automation handle repeatable paths while approval gates protect high-impact actions.

Principle 03

Measurable quality

Define accuracy, latency, review rate, failure rate, and business impact before launch.

Principle 04

Operational handoff

Document how the system runs, fails, recovers, and gets extended by the client team.

Process

What happens from here

01

Discovery and architecture

Weeks 1–4

We map all target workflows, design the full system architecture, and produce a build plan you review and approve before we start. Stakeholder alignment and sign-off is part of this phase.

02

Infrastructure and data layer setup

Weeks 5–6

Shared AI infrastructure, data integrations, security reviews, and baseline observability are laid down first — everything else builds on this.

03

Parallel workflow builds

Weeks 7–20

Multiple workstreams run simultaneously. You receive weekly updates and milestone demos throughout.

04

Integration, QA, and load testing

Weeks 21–28

All components are integrated and stress-tested against production-scale data volumes. User acceptance testing with real stakeholders before launch.

05

Training, documentation, and launch

Weeks 29–32

Team training, written documentation, and a staged launch. We stay on for 30 days to monitor and resolve.

Case Studies

Work covered by this service

Real engagements where this approach was applied — and the outcomes it produced.

AI Systems

Cross-Platform Commerce Orchestration

Agentic multi-merchant cart unification, cross-platform product sourcing, and fulfillment coordination — one checkout from any combination of merchants

5+Merchants unified
Read the case study
Commerce Platform

Event-Driven Commerce at $1M+ GMV

Moving from single-item checkout to a multi-item, event-driven microservices architecture that reached $1M+ annual GMV

$1M+Annual GMV
Read the case study
Modernization

Zero-Risk Legacy Modernization

AngularJS → Angular migration at enterprise scale using feature flags, strangler fig, and a shared design system — zero production incidents

0Incidents during migration
Read the case study
Get Started

Tell us about the transformation

Give us the big picture. We'll scope from there and come back with a realistic architecture proposal.

What happens after you submit

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Within 1 business day — You get a direct reply — not an auto-responder. We read every submission personally.
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Free 60-minute discovery call — We schedule a technical conversation. No sales pitch — we want to understand the actual problem.
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Honest assessment — If this engagement isn't the right fit, we'll say so and suggest what would actually help.
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Written proposal — If we're aligned, you receive a plain-language scope, timeline, and fixed price.

Name the systems we'd likely need to connect to.

I respond within 1 business day. No auto-replies, no sales calls without consent.

Not sure which service fits?

Start with a free workflow audit — it tells you exactly where to focus.

All ServicesSee Case Studies →