Sold by: New Math Data
An AI search layer across your documents and repositories that returns precise answers instead of a list of files.
Overview
Most enterprise search is still fundamentally broken. Teams chase down information across SharePoint, Confluence, file drives, ticketing systems, and internal databases, and even when they find what they are looking for, they still have to read through it to extract the answer. This engagement replaces that experience with an AI search layer, powered by AWS services like Amazon Bedrock, OpenSearch, and S3 Vectors, that understands context and returns precise, sourced answers.
- AI search layer connected to your existing data sources, repositories, and document systems
- Customized search experience tuned to your use case, from legal research to customer service
- API integrations feeding into broader AI workflows and tooling
- End-to-end data source mapping and indexing
- Workflow documentation for ongoing administration and extension
Key Benefits:
- Contextual answers that cut time spent searching
- Single interface across fragmented enterprise systems
- Compounds the value of existing AI investments
Best For:
Enterprises where information is fragmented across multiple systems and teams are losing meaningful time to poor search. Common entry points include legal, knowledge management, analytics, and customer service.
Timeline: 2 to 4 weeks to production. Pricing: Scoped per engagement. Contact us.
Highlights
- Unified search across all connected enterprise data sources
- Full deployment included: integration, indexing, customization, and API connectivity
- Applicable across legal, knowledge management, customer service, and analytics
Details
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