Transient DAF Container

WHAT DAF STUDIO IS

DAF Studio is the declarative operating system for production AI agents in capital markets. You declare what your workflows must do — DAF Studio orchestrates swarms of specialized agents to execute, with every action traced, versioned, and auditable end to end. The product is deployed inside your own Azure tenant, so your data, models, and proprietary signals never leave your boundary.

WHO IT'S FOR

DAF Studio is built for capital markets firms — asset managers, hedge funds, private equity, investment banks, and asset servicers — and the teams inside them that need AI to do real work, not just demo well.

- Front office: portfolio managers, research analysts, traders, and quant teams running research synthesis, deal analysis, idea generation, and signal hygiene.

- Middle office: risk, operations, and compliance teams running reconciliation, exception handling, attribution, and pre/post-trade controls.

- Investor relations and finance: teams producing LP reports, fund commentary, DDQ responses, and regulatory disclosures.

- CTOs and Heads of AI: technology leaders who own the path from AI pilot to production and need governance, auditability, and tenant-resident deployment to satisfy risk committees, regulators, and LPs.

THE PAIN IT ADDRESSES

Most enterprise AI projects in capital markets stall at the pilot stage. Three failures repeat:

- Governance gap. Pilots run on fragile prompt chains and screenshot-based audit. Risk committees, regulators, and LPs need attributable, replayable answers — and they don't get them.

- Data sovereignty. Sending proprietary alpha, client data, or trading signals to vendor-hosted endpoints is a non-starter for regulated firms. Most AI tooling assumes that's fine. It isn't.

- Integration drift. Demos work in isolation; production needs to plug into existing research stacks, OMS/PMS, data warehouses, and reporting pipelines. Generic copilots don't.

DAF Studio is built for that bar. Declarative configuration replaces fragile prompt engineering. Full audit trails replace trust-by-screenshot. Tenant-resident deployment replaces vendor data exposure. The result is the production path for AI in regulated capital markets.

THE THREE PILLARS

- Declare. Define workflows, constraints, guardrails, and outcomes once. DAF Studio compiles your declarations into running agent topologies and enforces every specification across every agent run.

- Execute. Orchestrate swarms of specialized agents that collaborate autonomously across your existing stack. Each agent has a narrow, accountable role coordinated through declarative pipelines you can read and reason about.

- Govern. Every agent action is traced, versioned, attributable, and replayable. Full explainability for LPs, auditors, regulators, and your own risk teams.

ARCHITECTURE AND TRUST

- Model agnostic. Bring GPT, Claude, Gemini, Llama, or your own fine-tuned models. Mix per task. No lock-in.

- MCP and A2A native. Built on Model Context Protocol and Agent-to-Agent standards. Plug in tools, data sources, and agents from the broader ecosystem.

- Your private cloud. Deploys inside your Azure tenant. Proprietary data never leaves your boundary.

- Zero retention. Your prompts, outputs, intermediate state, and proprietary data never train shared models or leak to third parties.

- Auditable by design. Every agent action — input, tool call, output, model version, timestamp, identity — is logged immutably and queryable.

GET STARTED

Subscribe through Azure Marketplace to begin. After purchase you'll be redirected to your DAF Studio command center to configure your first workflow. Enterprise plans include white-glove onboarding — our team works with you to declare, deploy, and validate your initial agent swarm in days, not months. Reference workflows for research synthesis, trade reconciliation, and LP reporting are available out of the box.

Questions, demos, or scoping? Contact sales@transient.ai or visit https://transient.ai.