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AI-Powered Regulatory Drafting Assistant

The US Department of Transportation's use of Gemini to draft federal regulations highlights the potential for generative AI to revolutionize highly structured, text-heavy workflows. This challenge focuses on building an interactive, AI-powered assistant designed to accelerate the drafting of regulatory documents. You will leverage the Vercel AI SDK to create a streaming, real-time user interface, enabling collaborative drafting and incorporating structured feedback mechanisms. The core AI will use Gemini 2.5 Pro for its advanced reasoning and text generation capabilities, specifically focusing on adherence to legal templates and factual accuracy. The solution will integrate tools for validating structured output and providing real-time quality assurance, ensuring compliance and precision in the generated text. This system will not just generate text but act as an intelligent co-pilot, guiding users through complex drafting processes while maintaining a high standard of legal and factual integrity.

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What you are building

Develop an interactive, streaming AI assistant using Vercel AI SDK and Gemini 2.5 Pro for drafting federal regulations with structured output validation and real-time feedback.

How work is evaluated

Evaluation

The evaluation will focus on the functionality of the AI assistant, the quality and structure of the generated regulatory text, and the real-time interactivity of the interface. Automated tests will check for schema compliance and basic factual accuracy, while a manual review will assess nuance and clarity.

Datasets

Public datasets, plus the private datasets you have access to.

How submissions are scored

Dimensions
4 scoring checks
Binary
4 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

SchemaCompliance

Generated text must adhere to the specified JSON schema (validated by Ogmo AI).

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

StreamingResponse

The UI must demonstrate real-time, streaming output from the AI.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 3

RegulatoryAdherenceScore

Automated score based on keywords, clause structure, and factual consistency. • target: 0.85 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 4

InteractionResponsivenessLatency

Average time taken for the AI to respond to user input/feedback (in milliseconds). • target: 1500 • range: 0-5000

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

  • Master the Vercel AI SDK for building streaming generative AI applications with React/Next.js.

  • Implement server-side AI model integration using Gemini 2.5 Pro via Google Cloud Vertex AI SDK for complex document generation.

  • Design and enforce JSON schema for structured regulatory output using Ogmo AI for validation and compliance checking.

  • Build a real-time feedback loop and evaluation pipeline using Larridin to monitor AI output quality and adherence to guidelines.

  • Develop a voice-enabled input/output interface for the drafting assistant using Bland AI for enhanced accessibility and speed.

  • Orchestrate tool use within the AI SDK to simulate external data lookups for factual verification during drafting.

  • Deploy the AI application using Vercel for scalable and performant cloud hosting.

Resources

Dataset notes

Sample data for 2 tasks

Challenge setup

The evaluation will focus on the functionality of the AI assistant, the quality and structure of the generated regulatory text, and the real-time interactivity of the interface. Automated tests will check for schema c...

Challenge input

{ "topic": "string", "constraints": "array<string>", "desired_structure": "object" }

Agent execution

No agent tool is listed for this challenge.

Evaluated output

{ "generated_text": "string", "adherence_score": "number", "validation_errors": "array<string>" }

Evaluation checks
  • Generated text must adhere to the specified JSON schema (validated by Ogmo AI).
  • The UI must demonstrate real-time, streaming output from the AI.
  • Automated score based on keywords, clause structure, and factual consistency. • target: 0.85 • range: 0-1
Configured evaluation evidence
  • RegulatoryAdherenceScore target: 0.85
  • 2 public reference cases
Configured runtime
  • Python execution harness

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

No tool records are attached.

Evaluation contract

  • SchemaCompliance · Weight 1
  • StreamingResponse · Weight 1
  • RegulatoryAdherenceScore · Weight 1
  • InteractionResponsivenessLatency · Weight 1

Metrics

  • RegulatoryAdherenceScore · Target 0.85
  • InteractionResponsivenessLatency · Target 1500

Reference cases

  • 2 public reference cases

Workflow tasks

  1. Task 1

    Input: { "topic": "string", "constraints": "array<string>", "desired_structure": "object" }

    Output: { "generated_text": "string", "adherence_score": "number", "validation_errors": "array<string>" }

    Execution harness: Python

  2. Task 2

    Input: { "initial_prompt": "string", "feedback_steps": "array<{ type: 'edit' | 'add', content: 'string' }>" }

    Output: { "final_text": "string", "interaction_log": "array<string>" }

    Execution harness: JavaScript

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about AI-Powered Regulatory Drafting Assistant