Many enterprise knowledge sources are too complex, structured, or interconnected for simple vector search to produce reliable results. For example, content such as tabular data, hierarchical structures, rules-based documentation, and documents with embedded logic or cross-referenced sections all require a deeper understanding of context and relationships. In some cases, multiple overlapping domains make it necessary to route the query before even beginning the retrieval process. Traditional AI chat solutions often return incomplete, inconsistent, or incorrect answers because they treat all content as unstructured text. This makes them unsuitable for high-trust use cases where nuance, precision, and explainability are essential.
Ingest structured documents, databases, tables, and domain-specific files. Avalon supports hybrid and graph-based indexing for maximum flexibility.
Choose or define multi-stage retrieval logic - such as keyword pre-filters, domain routing, or graph traversal - all through a low-code interface.
Define the agent’s tone, behavior, and rules for handling nuance and ambiguity. Guide how it prioritizes different types of sources or logic paths.
Enforce access policies, version control, and audit logging. Deploy via portal or widget, with enterprise-grade oversight built in.
Delivers relevant, context-aware responses by combining vector, keyword, and structural search methods.
Handles structured content, hierarchical relationships, and domain-specific rules with ease.
Applies access controls, audit logging, and version management across all retrieval stages.
Help teams navigate large technical manuals, procedures, and troubleshooting guides with targeted, high-confidence answers.
Make structured specs, component tables, and configuration logic searchable with precision — across complex data formats.
Ensure retrieval of sensitive, high-trust content is accurate, governed, and traceable — with logic that aligns to policy structure.
Curate and expose enterprise data from complex sources — without flattening or oversimplifying the original meaning or relationships.
© 2025, Zeaware Pty Ltd or its affiliates. All rights reserved.
