From kickoff to production AI in under 5 weeks.
Most AI projects die between proof of concept and deployment. Ours don’t — because we built our method around the gap that kills them.
Why 80% of AI pilots never reach production.
The failure mode is rarely the model. A proof of concept on a developer’s laptop can demonstrate value in days. What kills it is everything that happens next: the security review that flags unfiltered data access, the compliance team that demands audit trails no one documented, the IT leadership that wants integration architecture no one designed. Ongoing negotiations about enforcement timelines don’t change this dynamic — they extend the runway for doing it properly. The European Commission estimates that 5–15% of AI systems will fall into the Act’s high-risk category. By the time the governance work catches up, momentum is gone. The pilot becomes a deck. Our method starts with governance, not after it.
Seven steps. Five weeks. Production-ready AI.
Each step builds on the last. No parallel scramble, no governance retrofit.
Business Value Workshop
We spend two days with your leadership and business-line owners mapping where AI creates genuine leverage in your operation — and where it doesn’t. This is a diagnostic exercise grounded in ROI modeling, technical feasibility, and governance constraints. The goal is not brainstorming — it’s prioritization.
You leave with: A scored use-case portfolio and a recommended first deployment.
Data & Infrastructure Assessment
We map your data landscape: what exists, where it lives, who owns it, what’s sensitive, what’s accessible. We assess the technical feasibility of the chosen use case against your real infrastructure — not the ideal state. This phase surfaces the issues that kill projects later: undocumented data sources, unclear ownership, schemas no one has touched in five years.
You leave with: A documented data inventory and a feasibility-adjusted technical spec.
Hybrid Cloud & DevOps Design
We architect the right deployment model for your organization — fully managed cloud, private with enrichment, or pure sovereign. Networking, security zones, identity integration, CI/CD pipelines. We work with your existing infrastructure and security teams, not around them.
You leave with: An approved architecture diagram and a deployment plan signed off by your security function.
MLOps & Platform Setup
We configure WeavrCore on your infrastructure: knowledge ingestion pipelines, vector stores, LLM integration, monitoring, guardrails. By the end of this phase, WeavrCore is running end-to-end in your environment, consuming representative data from your actual systems. Depending on data sensitivity and volume, this may be a sampled subset or the full production set — what matters is that the integration is real.
You leave with: WeavrCore deployed, configured, and consuming production data.
Security, Compliance & Governance
We implement the governance layer that makes everything else auditable: data classification policies, role-based access, egress controls, EU AI Act documentation, audit trail configuration. This step is built into the timeline, not tacked on. The documentation produced here is what regulators will ask for.
You leave with: Complete EU AI Act technical documentation and an audit-ready governance configuration.
PoC Delivery & Business Validation
We deliver a working proof of concept on your real data, validated against the KPIs you defined in Step 01. Your business users interact with it directly. Your compliance team reviews its audit trails. If something needs to change, this is where we catch it — not after launch.
You leave with: A PoC that your business and compliance teams have both approved.
Production Launch & Scale Plan
We promote the PoC to production, integrate it into the workflows it’s meant to support, and train your teams. Then we help you plan the next deployment — more departments, more use cases, more data sources. Because the foundation is already in place, subsequent deployments compound off the first.
You leave with: Production AI in active use, and a 6-month roadmap for the next three deployments.
The 5-week view at a glance.
Steps overlap where preparation for the next phase begins before the current one completes. This is the rhythm of fast, governed delivery.
This is the typical cadence for a single use-case deployment. Complex engagements with multiple data sources or regulated industries typically extend by several weeks.
Why we can move this fast.
Three things have to be true for a 5-week timeline to be real. Here’s what they are.
Senior-only teams
Every engineer on your project is a senior specialist — 10+ years of experience in their domain. No juniors learning on your timeline. No pyramids where 20% of the people do 80% of the work. The senior-specialist model costs more per hour; it costs less per project.
Governance from day one
Compliance is the first step, not the last. Our timeline assumes you will need EU AI Act documentation, audit trails, and role-based access — and builds them in from the architecture phase. The European Commission’s own impact assessment puts enterprise compliance costs at €180K–€420K per high-risk AI system, much of it in architectural and governance work that is expensive to retrofit. Building it in from the architecture phase avoids months of rework.
A platform, not a custom build
WeavrCore is the same platform across every engagement. Your implementation is configured, not built from scratch. The patterns are proven. The platform is stable. The timeline reflects that.
The numbers behind the method.
Our team has been delivering production AI since 2024 — across European public sector, regional government, and commercial operations. Client names withheld under NDA. See the Platform page for deployment stories.
Want to see what this looks like for your organization?
A walkthrough is 30 minutes. No prepared pitch, no product deck — we look at your situation and tell you honestly whether our approach fits.