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    8nap AI CoCo – Conversations with Complex Data

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    Sold by: Zimetrics 
    Enable users to interact with structured data of enterprise in a conversational way, Transform user query into SQL queries for information retrieval, Fine tune LLM models to understand underlying schema, Modularized data pipelines with security controls

    Overview

    8nap AI CoCo by Zimetrics is an enterprise-grade conversational AI platform designed for natural language interactions with structured and unstructured data sources. It powers business intelligence, self-service bots, and customer support automation by enabling contextual, real-time dialogue with backend systems. Built on schema-aware models and pre-engineered data connectors, CoCo ensures scalable, secure, and domain-optimized performance with reduced token costs. Enterprises benefit from faster decision-making, lower support loads, and intuitive access to insights—all without requiring complex BI tools or dashboards.

    Features:

    • Pre-Engineered Connectors for Complex Data Sources Enables quick integration with diverse backend RDBMS for real-time data interaction.

    • Schema-Aware Models with Fine-Tuning Reduces token consumption and enhances response relevance with optimized schema-aware language models.

    • Guardrails for Enterprise-Grade Security Built-in RBAC and access policies safeguard sensitive data during conversations.

    • Conversational Workflows with Contextual Memory Supports multi-turn conversations, configurable business logic, and intelligent follow-ups through feedback loops.

    • Conversational Reporting Blends Retrieval-Augmented Generation with structured data for on-demand conversational reporting and insights visualization.

    • LLM-Powered Chat Interfaces Prebuilt chat interface, with chain of thought traceability

    Key Implementation Details:

    1. Model Finetuning: LLM model is fine-tuned with Sage Maker for database schema adaptation. LLM available on Bedrock is leveraged to generate synthetic training data based on existing schema.

    2. Storage & Knowledge Management: Amazon S3, EFS, and Aurora are used for storing documents, shared data, and structured metadata. Amazon OpenSearch serves as the vector store, while AWS Glue manages metadata via a central data catalog. Secrets are securely stored in AWS Secrets Manager with encryption handled by AWS KMS.

    3. API & Network Infrastructure: Amazon Route 53 with ACM provides a unified entry point via Amazon API Gateway. Internal services are exposed through a private Application Load Balancer using VPC Link.

    4. Authentication & Access Control Amazon Cognito manages authentication and authorization for user access across the platform.

    5. Monitoring & Observability Monitoring and logging are enabled through Amazon CloudWatch, AWS CloudTrail, and the ELK stack.

    Highlights

    • Fine-tuned schema-aware execution for cost-efficiency
    • Transparent decision chains with traceable execution logic
    • Optimized for low latency, high performance interactions, high customizability and model ownership

    Details

    Delivery method

    Deployed on AWS

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