Kolleno
AI-driven accounts receivable automation to accelerate cash flow and optimize collection workflows.
The Intelligence Layer for Global Financial and Professional Services Data.
Kensho, an S&P Global company, is a premier AI laboratory specializing in machine learning and natural language processing for the financial sector. Its 2026 technical architecture is centered around the 'Financial Knowledge Graph,' a massive, interconnected data structure that links disparate datasets to S&P Global's master identifiers. The platform excels at processing complex, jargon-heavy financial documents where general-purpose LLMs often falter. By utilizing specialized models like Kensho Scribe (speech-to-text for financial calls) and Kensho NERD (Named Entity Recognition and Disambiguation), the system provides high-fidelity data extraction that maps directly to Capital IQ and GlobalID ecosystems. In the 2026 market, Kensho positions itself as the mission-critical middleware for financial institutions building autonomous AI agents, providing the structured 'ground truth' data required to mitigate hallucinations in RAG-based systems. Its infrastructure is built for massive scalability, supporting high-throughput API demands for the world's largest investment banks and regulatory bodies.
Named Entity Recognition and Disambiguation that links 100M+ entities to a unique GlobalID.
AI-driven accounts receivable automation to accelerate cash flow and optimize collection workflows.
Institutional-grade AI-driven investment strategies and quantitative risk management through the Marquee platform.
Precision algorithmic engine for institutional-grade price-gap detection and real-time market dislocation analysis.
AI-powered cash flow forecasting and intelligent credit control for SMEs.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Deep learning-based speech-to-text engine specifically trained on over 100,000 hours of financial earnings calls.
A sophisticated data-matching tool that cleans and maps messy internal data to institutional-grade datasets.
ML-driven OCR and table extraction that understands the layout and context of financial reports.
NLP classification engine tuned for financial sectors and industry themes (GICS).
Native integration with S&P Global's universal entity identifier system.
A 2026-era graph database connecting entities, people, and events with temporal awareness.
Manual transcription and analysis of earnings calls are slow and error-prone.
Registry Updated:2/7/2026
Summarize sentiment using fine-tuned financial models.
Consolidating multiple internal databases with inconsistent company naming conventions.
Identifying companies involved in emerging sectors like 'Green Hydrogen' before they are officially tagged.