RAGs empower Agents to generate fact-based, contextually accurate responses by combining LLM reasoning with real data from trusted sources. This integration ensures every output is informed, relevant, and grounded in real-world information.
Combines retrieval with generation.
Enhances context-aware agent responses.
Reduces LLM hallucination risks.
Ensures data-backed decision-making.
RAGs integrate smoothly with Syncloop Knowledge Bases and LLMs to deliver unified intelligence. Agents can instantly retrieve relevant data from connected knowledge sources and use it to enhance their reasoning and output quality.
Instant data retrieval from sources.
Works with Knowledge Bases and LLMs.
Unified access across all agents.
Strengthens multi-agent collaboration.
RAGs improve accuracy and trust in AI-driven workflows by grounding responses in verifiable data. Integrated directly into multi-agent systems, they ensure reliable insights, consistent logic, and smarter decision-making across the entire Syncloop workflow.
Improves AI accuracy and trust.
Ensures reliable, verifiable insights.
Maintains workflow consistency.
Drives smarter automation decisions.
Fintechs must continuously detect, investigate, and report suspicious activity across high-volume transactions.
Onboarding demands fast, accurate identity verification across documents, liveness, address proofs, and database checks.
Managing multiple utility bills (electricity, water, gas, internet, phone, etc.) is a repetitive and error-prone task.
In modern e-commerce, retailers often sell across multiple channels such as Amazon, eBay, etc. and their own websites.
We have put together some commonly asked questions
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