Rainbird
  • 🏃‍♂️Getting started
    • What is Rainbird?
    • How does Rainbird work?
    • Example use cases
      • 📈Investment suitability assessment
      • 🤖Digital tax consultant
      • 🏥Covid risk assessment
      • 🚗Insurance claims liability
      • 💰Fraud identification
    • Hosting options
    • Quickstart guide
    • Onboarding with Rainbird
  • 🧠Knowledge Modelling
    • What is knowledge modelling?
    • What is a query?
    • Modelling
      • Concepts
        • Concept instances
      • Relationships
        • Question Configuration
        • Rules
          • Match, Infer, Ask process
          • Expressions List
      • Facts
      • Datasources
      • Other features
        • Markdown
        • Import/Export Knowledge Maps
      • Troubleshooting Tips
    • Testing
      • Manual tests
      • Automated tests
      • External User Acceptance Testing (UAT)
    • Versioning
    • Publishing
      • API Management
      • Setting a live version
      • Publishing an agent
    • Stats and Reporting
    • Managing your data
    • The library
      • How to: update a template
  • 🔍Evidence
    • What is evidence?
    • The Evidence Tree
      • The Salience Chart
  • 👩‍💻Developer guides
    • Overview
    • API Guide
      • API request flow
      • Run example queries
      • Environments
      • Error codes
      • Skipping an answer to a question
      • Retrieving a full Evidence Tree for use with a custom UI or application
      • Building an Evidence Tree URL
    • API interactive documentation
    • SDKs
  • Rainbird Labs
    • Overview
    • Consult
    • Generate from documentation
    • Co-author
    • /interact
    • /explain
Powered by GitBook
On this page
  • Knowledge Elicitation
  • Consult (open beta)
  • Knowledge Representation
  • Generate from documentation (under development)
  • Co-author (closed beta)
  • Noesis (under development)
  • Reasoning
  • /interact (open beta)
  • Explainability
  • /explain (open beta)
  1. Rainbird Labs

Overview

Last updated 3 months ago

Rainbird Labs: Combining the power of knowledge representation and reasoning (KR&R) with Large Language Models (LLMs) to deliver explainable and trustworthy AI.

All features delivered by Rainbird Labs are beta. They may contain bugs, are subject to change and are not covered by our platform SLAs.

Knowledge Elicitation

Consult (open beta)

Speak with a digital Knowledge Engineer at Rainbird Consult to help flesh out your decision domain. This tool supports knowledge elicitation by extracting tacit expert knowledge through a guided consultation. Documentation can also be uploaded where it is relevant to the consultation.

A detailed report summarising the knowledge and expertise captured is produced, which can be reviewed by experts and used to build the knowledge graph.

Knowledge Representation

Generate from documentation (under development)

Generate a knowledge graph from documentation. Works best when using a Rainbird Consult report and/or documentation that clearly describes processes and rules.

Co-author (closed beta)

An agent that can support with modifications to, and explanations of, your knowledge graph to support in refinement.

Noesis (under development)

A fine-tuned LLM dedicated to generating Rainbird knowledge graphs from unstructured data, complete with a set of Python APIs to integrate directly into ML pipelines.

Reasoning

/interact (open beta)

Interact is an API to provide data and query your knowledge graph in natural language to get deterministic results.

Where the reasoning engine asks questions to gather more data (from human or AI agents), the answers can be posted back via interact when using the same session.

Explainability

/explain (open beta)

Use the explain API endpoint to obtain natural language explanations for any decision provided to provide further details to the end-user or add to reports.

and join the early access programme.

Learn more
Learn more
Learn more
Learn more
Learn more