Most firms sell you one rung of the ladder.
Consultancies advise, then leave. Product vendors hand you software, then a support queue. Mezza does all four rungs under one engagement and one standard of governance.
The expensive part of AI projects is the seams.
When the strategy firm leaves, the build firm rediscovers your data problems at full rate. When the vendor’s product meets your stack, the integration becomes your problem.
On Mezza engagements, the people who mapped your data in advisory are accountable for the system that runs on it two rungs later. Context survives because the team does.
Advise. Build. Integrate. Run.
Advise
Strategy and feasibility, grounded in your data and your mandate, with governance costed in from the start.
- A data and systems assessment your engineers will recognize as accurate.
- Use cases ranked by value and feasibility, including the ones we advise against.
- A sequenced roadmap with effort, dependencies, and decision points.
- A document you own outright. Take it to any builder, including not us.
We set the timeline together in the first meeting. Leads to Build, or a clear decision not to.
Build
Finance-native engineering. Data pipelines, models, and agentic workflows built for your use case, documented to the standard a model-risk function expects.
- Working systems on your data, validated out-of-sample where models are involved.
- Documentation written for two audiences: your engineers and your examiners.
- Source-linked, auditable outputs as the default architecture, not an upgrade.
- Your data stays yours. We never train models on it for anyone else.
Leads to Integrate, once the build earns its place in the real workflow.
Integrate
Landing the system where work actually happens: your portfolio tools, your casework queues, your product’s API. Drakkar where it fits, bespoke where it does not.
- AI inside your existing systems, entitlements, and approval flows.
- Human-approval gates wired into your escalation paths, not bolted on after.
- Your team trained on interrogating the system, not just operating it.
- A cutover plan your change-management process can live with.
Leads to Run, or handover to your team with our documentation.
Run
Managed operation under your governance. The system stays accountable after the launch applause stops.
- Monitoring for model drift, data breaks, and behavior changes, with explained alerts.
- Scheduled validation and retraining cycles, documented for your records.
- Incident response with named owners and post-incident reports.
- Decision logs maintained continuously, ready for internal audit or examiners.
The ladder is a loop in practice: running systems generate the evidence for the next advisory question.
We automate the evidence. You keep the verdict.
At every rung, the boundary is the same: Mezza’s systems retrieve, reconcile, test, and propose. Your people decide.
We believe that boundary is not a temporary concession to regulation. It is the correct architecture for financial decisions, where accountability must always trace to a person. Bounded autonomy is written into everything we build, which is why our systems log decisions instead of hiding them.
Start where you actually are.
Exploring. You want a credible map before any commitment. Start with Advise.
Schedule a meetingBuilding. You know the use case. You need finance-native engineers who assume the audit. Start at Build.
AI integrationReady for the platform. You want research, risk, and allocation on one governed data layer. Start with a Drakkar demo.
Explore Drakkar
First meeting: your situation, mapped to the ladder.
You describe where AI sits in your firm today. We tell you which rung we would start on, what it would involve, and what we would not do. Plainly.