Coforge_Insightiq_Agent
Chat-based analytics for fast, intelligent data insights
External enrichment · as of 2026-08-29
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Chat-based analytics for fast, intelligent data insights
Helps underwriter to automatically analyze the inspection report so as to optimize the overall time.
It is an accelerator for automating data extraction and analysis from Insurance Application document
AI-powered assistant ensuring clean, secure, and compliant code delivery
AI-powered automation for faster, compliant software change management
AI assistant that accelerates claims validation, assessment, and communication
AI-powered agent for intelligent loan document extraction, validation, and risk checks
AI research assistant delivering real-time market, competitor, and trend intelligence
AI assistant that automates research synthesis, insight generation, and report creation
Adaptive AI search assistant for fast, context-aware knowledge discovery
Streamlines HR processes efficiently.
Coforge – Nebulon: Marketing Agent accelerates marketing content generation with AI
The Agentic Data Quality Resolver is an AI-driven data reliability platform that proactively detects, investigates, and remediates data quality issues across modern AWS-based data platforms. Using a coordinated Agentic AI architecture, the solution deploys multiple specialized AI agents—each focused on specific data quality dimensions such as completeness, accuracy, validity, timeliness, and uniqueness. These agents collaborate to identify defects, diagnose root causes, and recommend or execute governed remediation actions. Powered by Amazon Bedrock for LLM reasoning and deployed on Amazon EKS for enterprise scalability, the platform resolves issues such as missing values, schema inconsistencies, duplicates, invalid formats, stale data, and referential integrity violations. It helps organizations shift from reactive monitoring to proactive, intelligent, and governed data quality resolution.
Auto Data Mapping is an AI-powered intelligent accelerator that simplifies and accelerates complex data modeling and mapping across legacy and modern data landscapes. It leverages AI to automatically suggest accurate source-to-target data mappings, features an intuitive visual mapping canvas for schema mapping and transformation design, provides end-to-end data lineage graphs for full traceability, and supports flexible schema management via CSV ingestion or manual input. Reduces data mapping effort by 50%, improves team productivity by 45%, and cuts mapping errors by 40% through AI-driven validation. Deployed on AWS using Amazon EKS with integration to Amazon S3, Amazon Redshift, and Amazon Bedrock for AI-powered mapping intelligence. Part of Coforge Data Cosmos™ – the innovation backbone comprising platforms, agents, and services that accelerates execution across every phase of the data lifecycle.
BricksOps is a Coforge Data Cosmos™ accelerator that unifies Databricks operations, governance, and observability into a single control plane. It automates workspace discovery, repository-to-job traceability, governance monitoring, and cluster optimization recommendations, eliminating manual tracking and fragmented tools. Built on AWS (Amazon EKS, S3, and Databricks) with GitHub Actions integration, it accelerates insights from hours to minutes, improves audit readiness, reduces operational effort, and optimizes cluster costs.
Code Conversion Agent is a multi-agent AI system that converts DDL, DML, SQL stored procedures, and transformation code from legacy platforms to modern cloud-native data stacks. It ingests source code from SSIS, Informatica, Oracle, SQL Server, and other RDBMS/EDW platforms and converts to 20+ modern targets including dbt on Snowflake/Databricks/BigQuery, PySpark on AWS Glue/Databricks, and native SQL for Snowflake/BigQuery/Redshift. The conversion runs through a 4-stage multi-agent pipeline: Lineage Agent (data flow diagrams), Conversion Agent (target syntax), Validation Agent (correctness and logic fidelity), and AutoFix Loop (automatic retry and patching). Supports Google Gemini, OpenAI GPT-4o, Anthropic Claude, and local Ollama. Delivers source vs. target code, validation reports, lineage diagrams, and confidence scores.
Data Object Analyzer is an AI-powered database discovery, diagnostics, and performance insights technology artifact for enterprise database landscapes. Part of the Coforge Data Cosmos platform, it provides a unified interface for automated database scanning, schema profiling, health checks, and query optimization — replacing fragmented tooling and manual SQL scripting with proactive database management. Core capabilities include an Automated DB Scanner for instant server discovery, Smart Recommendations with severity-tagged query optimization advisory, Deep Diagnostics with a 6-tab view for health, schema, and profiling, and an AI Chat interface (MCP) for natural language data interaction. Reduces environment setup time by 70% and consolidates monitoring into a Smart Dashboard.
Coforge Data Quality Framework follows a 4-phase lifecycle — Assess (information needs, data profiling, baseline DQ metrics), Plan (DQ vision, rules design, cleansing strategy, scorecard KPIs), Innovate (deploy Coforge Agentic DQ resolver technology artifact, ML-based entity resolution, GenAI rule generation), and Execute (automated correction, centralized rules engine, DQ dashboards, continuous AI/ML monitoring, knowledge management). Operates under enterprise governance (policies, stewardship, standards) with business needs driving priorities. Integrates with business teams through a Business Case & Change Council. Deployed on AWS with Amazon EKS, Amazon Bedrock, AWS Glue, and Amazon S3.
Kepler is an AI-driven, cloud-native healthcare contract intelligence platform that ingests, analyze, and operationalizes complex provider–payer contracts at scale. The platform uses OCR, NLP, clause normalization, and AI-based risk scoring to transform unstructured contract documents into structured, analytics-ready datasets. Built on AWS managed services including Amazon EKS, Amazon S3, Amazon Aurora PostgreSQL, Amazon DynamoDB, Amazon Textract and Amazon Bedrock, Kepler delivers secure, multi-tenant SaaS capabilities aligned to healthcare compliance requirements. It correlates contract terms with historical claims and financial datasets to detect revenue leakage, identify compliance gaps, and highlight negotiation opportunities. Kepler provides HIPAA-aligned security, role-based access control and full auditability for enterprise healthcare operations.
Ticket Analyzer is a Coforge accelerator that transforms how teams interact with support tickets using a chatbot powered by Retrieval-Augmented Generation (RAG). By combining LLMs with enterprise ticket data, it retrieves relevant historical tickets and generates context-aware, accurate responses — enabling teams to move from manual search to AI-driven, insight-led support. Key capabilities include a RAG-powered intelligence engine, conversational AI interface for natural language ticket exploration, contextual resolution engine surfacing past resolutions and root causes, pattern and trend analyzer identifying recurring issues, and real-time analytics for instant ticket insights. Delivers 30–50% faster issue resolution, 40%+ knowledge reuse, and 25–35% efficiency gain with reduced SME dependency.
Forge-X, AI-forward engineering platform, accelerates portfolio modernization and application lifecycle management with modular, domain-aligned components that deliver agility, accuracy, and business-aligned outcomes.
Huge Data Publicly Available need to be Analyzed by investment management companies & department.