The intelligence layer for financial decisions.
Mezza AI builds AI systems for financial firms and runs them with you. They turn your data into decisions you can defend.
Built on your data. Never used to train models for anyone else.
- 12,400 sh
- Flagged: 12,380 sh
- 12,400 sh
OMS is the trade-date book. 20 sh settle tomorrow at the prime broker.
Rebalance 3 names as planned. No break on ACME.
OMS blotter, fill 14 (trade date) and 2 more sources
Waiting for the portfolio manager
We take you from the first question to a system in production.
One partner. Enter at any stage. Stop after any stage.
Advise
A written plan and a straight answer on readiness.
Build
Working systems running on your own data.
Integrate
AI inside the tools your team already uses.
Run
A system that stays accountable after launch.
One method, two kinds of company.
Automation embedded in infrastructure, not AI bolted on. We learned it in finance, where errors are expensive.
Financial institutions
Our focus: research, risk, and allocation on governed data.
Startups and mid-sized companies
A higher level of automation, on the systems you already run.
Most firms are piloting AI agents. Few have them in production.
The model is rarely what stops them. The same record sits in three systems. The three do not agree.
52%piloting AI agents
19%deploying AI agents
Everything arrives at once.
Agents read each item.
One data layer takes out what matters.
Analysis, ready for a person to decide.
How the system handles a decision.
Four duties make an intelligence layer. Use them to test any vendor, including us.
Assemble
Only the filings, positions, and constraints this decision needs enter the model’s window.
Remember
Constraints, prior decisions, and granted exceptions carry across sessions.
Orchestrate
Research, risk, and compliance agents work in parallel. Thin evidence sends the loop back.
Account
Sources, reasoning, alternatives, and the sign-off stay on the decision record. Rejected proposals stay too.
You decide how far the system acts alone.
Autonomy is earned, one control at a time.
Agent: Acts inside policy limits encoded as machine-checked rules.
Your team: Sets and signs the mandate. Reviews behavior on a cycle.
Agent: Executes a multi-step workflow after explicit approval.
Your team: Approves the plan. Can stop it at any step.
Agent: Proposes a specific action and shows its evidence.
Your team: Decides. Signed off or rejected, the call is logged.
Agent: Drafts tearsheets, memos, and reconciliation summaries.
Your team: Owns every artifact that leaves the desk.
Agent: Answers questions over governed data and cites its sources.
Your team: Does the work. The agent compresses the search.
Drakkar is our platform for research, risk, and allocation.
It is the intelligence layer as a product. Every module works from the same reconciled data and the same memory.
Start where you are.
No clean data required. The first conversation is about one decision and the data you have today.
A few lines from you. A working session. A written answer.