Avarrai is building an execution intelligence infrastructure for capital markets, connecting fragmented market data, workflow context, and institutional knowledge with governed AI to support smarter trading decisions. The platform integrates with existing O/EMS systems and trading workflows, delivering explainable recommendations while preserving human control and accountability. It is initially applied to fixed income markets, where fragmented liquidity and scattered signals create the greatest need for structured execution intelligence.
Funding
Funding not disclosed
Founders
Product
Problem
Institutional trading desks face fragmented market data, scattered liquidity signals, and multiple execution protocols that make it difficult to assess whether, when, and how to execute trades. More data and more systems have not produced better-informed decisions, leaving traders without a unified view of market context, workflow history, and institutional knowledge at the point of decision.
Solution
Avarrai provides an execution intelligence layer that sits across the existing trading stack, connecting client-controlled systems with market-authoritative data sources. The platform normalizes fragmented context into canonical views, evaluates execution choices across timing, price, counterparties, venues, and protocols, and returns structured, explainable recommendations into trader interfaces, O/EMS workflows, and APIs. A deterministic control plane governs permissions, policy checks, and model boundaries, ensuring that AI recommendations remain within defined guardrails while keeping accountability with the trading desk. The platform captures execution evidence and connects outcomes back into the system so intelligence improves through use, all without replacing existing systems of record.
Target Audience
Primary customers are institutional trading desks, execution teams, and buy-side and sell-side firms in fixed income markets, as well as O/EMS providers and market infrastructure participants seeking to integrate execution intelligence into their workflows.
Features
- Market and liquidity intelligence that interprets market conditions, liquidity signals, and execution context to identify actionable opportunities
- Execution decision intelligence evaluating timing, price, counterparties, venues, protocols, and execution strategies with structured recommendations
- Execution orchestration coordinating routes, workflow steps, escalation paths, fallback behavior, and decision hand-offs across execution channels
- Governed recommendations with reason codes, confidence scores, and evidence, supported by a deterministic control plane for permissions, policy checks, and model boundaries
- Execution evidence capture that records context, reasoning, and outcomes for auditability and oversight
- Execution learning loop that connects recommendations, overrides, workflow actions, and outcomes to improve future intelligence within governance frameworks
- SaaS-first deployment with models designed for different institutional, operational, and sovereignty requirements