Meet FireFlow, the execution layer for financial institutions
Deterministic orchestration infrastructure to deploy regulatory-grade, perimeter-contained AI agents rails in weeks, not years.
Finance is entering an infrastructure transition
Not a product transition
Intent-Driven
Yesterday
The customer opens an app. Browses. Clicks. The customer is the executor of intent. Brand and distribution scale dictate market power.
Navigational
Today
An AI agent resolves intent on their behalf. It does not see brand. It executes against whichever infrastructure answers its call.
AI is redefining the very nature of how we do business over internet
Don't become a node
Rely on third-party orchestration. Become progressively invisible to AI agents routing on behalf of customers. Zero leverage against displacement.
Own the rails
Deploy deterministic orchestration infrastructure. Become an addressable, governed execution node in the agentic commerce ecosystem. Capture structural value.
In-housing AI readiness without support comes with significant overhead
$5m+
Direct Build Cost
Estimated sunk cost for in-house deterministic infrastructure before going live.
85%
Budget Overrun
Of organizations misestimate AI costs by more than 10%. (Benchmarkit)
80%+
Failure Rate
Of AI projects fail—roughly twice the failure rate of non-AI IT projects. (RAND Corp)
Composable Agent Platform
Beyond safety - the platform layer institution teams build on directly.
Visual flow builder & reusable library
What it does
Institution teams author agents through a graphical builder. Flows are versioned, modified and reused across the institution.
Why it matters
Agent development moves out of engineering backlogs. Each workflow becomes a permanent institutional asset, not a one-off integration.
Native MCP / Skills / CLI integration
What it does
Any machine-readable service becomes a tool the institution owns.
Why it matters
Reusable Skills package these tools into workflows deployed across business lines.
Multi-agent orchestration
What it does
Agents work together on complex tasks, delegating sub-tasks to specialised agents.
Why it matters
Cross-system, multi-step workflows under a single governed flow with hard limits.
Context-aware routing
What it does
A smart router invokes the right specialised agent based on user intent.
Why it matters
No manual handoff logic; one conversational entry point connects to dozens of capabilities.
Deploy governed, compliant execution surfaces
Standard workflow tools fail in regulated environments because they lack transactional guarantees. FireFlow is built specifically for irreversible, high-stakes financial operations.
High-Value Transactions
Payments, transfers and settlements where the agent prepares everything but a human approves execution. The workflow pauses for minutes or days and survives any infrastructure event.
Sandboxed Execution
Agents run in isolated environments with only the permissions they need. A misbehaving agent cannot reach beyond its scope into other workflows, the host or external data.
Multi-Agent Orchestration
A single request requiring several specialised agents: pricing, eligibility, documentation, execution. A smart router invokes each in sequence under one governed flow.
Disputes & Audits
When a customer or regulator questions an outcome, the full decision can be replayed step by step. Every input, every action, reproducible months later.
Controlled Agents
The AI talks; the workflow decides what it can actually do. Available actions, order and permissions are locked in advance outside the model's control.
On-Premise LLM
The AI model runs inside the institution's own infrastructure. Customer data, transactions and internal documents stay inside the perimeter never sent to an external API.
High-Value Transactions
Payments, transfers and settlements where the agent prepares everything but a human approves execution. The workflow pauses for minutes or days and survives any infrastructure event.
Sandboxed Execution
Agents run in isolated environments with only the permissions they need. A misbehaving agent cannot reach beyond its scope into other workflows, the host or external data.
Multi-Agent Orchestration
A single request requiring several specialised agents: pricing, eligibility, documentation, execution. A smart router invokes each in sequence under one governed flow.
Disputes & Audits
When a customer or regulator questions an outcome, the full decision can be replayed step by step. Every input, every action, reproducible months later.
Controlled Agents
The AI talks; the workflow decides what it can actually do. Available actions, order and permissions are locked in advance outside the model's control.
On-Premise LLM
The AI model runs inside the institution's own infrastructure. Customer data, transactions and internal documents stay inside the perimeter never sent to an external API.
High-Value Transactions
Payments, transfers and settlements where the agent prepares everything but a human approves execution. The workflow pauses for minutes or days and survives any infrastructure event.
Sandboxed Execution
Agents run in isolated environments with only the permissions they need. A misbehaving agent cannot reach beyond its scope into other workflows, the host or external data.
Multi-Agent Orchestration
A single request requiring several specialised agents: pricing, eligibility, documentation, execution. A smart router invokes each in sequence under one governed flow.
Disputes & Audits
When a customer or regulator questions an outcome, the full decision can be replayed step by step. Every input, every action, reproducible months later.
Controlled Agents
The AI talks; the workflow decides what it can actually do. Available actions, order and permissions are locked in advance outside the model's control.
On-Premise LLM
The AI model runs inside the institution's own infrastructure. Customer data, transactions and internal documents stay inside the perimeter never sent to an external API.
Leadership
Co-Founder
Mike Sarvodaya
Former propshop and fund quant risk manager. Driving institutional digital asset strategies since 2016 and pioneering advanced AI-driven solutions since 2022.
Co-Founder
Vladimir Maslyakov
Built one of the fastest-growing Web3 exchanges with 100M+ users.
Co-Founder
Max Rabinovitch
Led growth of Chiliz ecosystem to 70+ global sports organizations.
Explore how Fireflow can help
Conduct a 4 week assessment of the institution's current infrastructure, regulatory posture, and integration scope followed by a proposal for a staged deployment.
