SOLVE aggregates 24+ million daily quotes across hundreds of thousands of securities—covering all major fixed income asset classes. Our state-of-the-art parsing technology transforms unstructured messages into clarity, giving professionals unmatched transparency into pre-trade market activity.
Fixed income markets are fragmented. Quotes arrive in every format, from every desk, across every corner of the market. Most platforms require structured inputs before the data can be used. Traders end up stitching signals together — or trading without a full view.
SOLVE changes that. SOLVE Quotes ingests 24M+ raw, unstructured quotes each day across every major fixed income asset class, parsing them into structured data that delivers clarity and transparency into markets that are otherwise opaque.
Coverage
Daily Securities
Daily Quotes
AI Predictive Trade Prices
Coverage
Daily Securities
Daily Quotes
Coverage
Daily Securities
Daily Quotes
Coverage
Daily Securities
Daily Quotes
AI Predictive Trade Prices
Coverage
Daily Securities
Daily Quotes
Coverage
Daily Securities
Daily Quotes
Coverage
Daily Securities
Daily Quotes
Gain visibility across 24M+ daily quotes parsed, normalized, and structured from unfiltered market color—spanning the full fixed income landscape, including bonds, loans, munis, and structured products.
SOLVE Quotes turns fragmented dealer messages into structured, comparable data that supports accurate price discovery and informed decision-making.
Identify best levels, fill axes, and manage inventory with precision using aggregated and normalized dealer color. Powered by SOLVE’s proprietary NLP Parsing Engine, SOLVE Quotes structures millions of unformatted dealer messages into actionable data that reflects real-time fixed income market activity.
Win client trust with transparent, defensible data that validates market assumptions and pricing decisions. SOLVE Quotes arms sales and trading desks with objective market color that supports conversations, deepens relationships, and improves pricing outcomes.
Feed quant strategies, analytics engines, and valuation processes with clean, observable quote data. The normalized dataset integrates directly into enterprise systems and pricing models, ensuring consistency and transparency across front-office and valuation teams.
Monitor shifts in bids, offers, and spreads across issuers, sectors, and structures. SOLVE Quotes provides the real-time transparency needed to assess changing conditions and identify potential value opportunities using observable data.
Monitor axes, BWICs, and market shifts in real time to respond quickly and with confidence. By transforming billions of unstructured messages into structured, actionable data, SOLVE Quotes gives professionals the transparency needed to recognize changes and trade with confidence.
Aggregate observable quotes and composite pricing to validate levels in illiquid markets.
Leverage NLP and AI to extract bids, offers, sizes, and market color from unstructured messages — transforming billions of raw dealer quotes into structured, usable market data.
Evaluate comparable bonds and securities using composite and historical quote data to understand pricing context across issuers and sectors.
Monitor BWICs, inventory, and intraday quote activity with live updates and visualization tools that reveal shifts in liquidity and dealer activity.
Purpose-built to read and structure unstructured dealer messages from email quote traffic—extracting bids, offers, sizes, and market color at scale.
Aggregates 24M+ daily quotes across 250K+ corporate bonds, 1.1M+ municipals, syndicated loans, and other asset classes—providing a consolidated view of fixed income activity.
Standardizes incoming quotes from hundreds of contributors, aligning formats, fields, and identifiers into one unified data structure.
Records every parsed quote with timestamp and source metadata, enabling historical trend analysis, audit trails, and backtesting.
Links quotes across bonds, loans, and related instruments to support benchmarking, portfolio monitoring, and relative market comparison.