Challenge

Development Underwriting Engine with CrewAI & NVIDIA NeMo Guardrails

Major developers restarting capital deployment need rigorous risk screening across volatile market and construction signals. Build a CrewAI multi-agent engine wrapped in NVIDIA NeMo Guardrails to synthesize zoning rules, submarket cap rates, and supply-chain risk without hallucinated metrics.

Business OperationsHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Orchestrate specialized underwriting roles in CrewAI with NVIDIA NeMo Guardrails safety policies governing financial metric outputs.

Delivery guide

How work is evaluated

Evaluation

Evaluates feasibility analysis correctness and checks that NeMo Guardrails block invalid financial metrics.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

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

guardrail_hallucination_block

Verifies output cap rates are constrained between 2% and 15%

Binary check

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

Dimension 2

memo_accuracy_score

Accuracy of financial ratio calculations against ground truth math models • target: 0.95 • range: 0-1

Binary check

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

Learning goals

What you should walk away with

  • Build a multi-agent crew (Zoning Analyst, Financial Modeler, Risk Manager) using CrewAI.

  • Define programmable rails in NVIDIA NeMo Guardrails to validate cap rate and debt yield ranges.

  • Synthesize real estate deal proposals into structured feasibility memos.

  • Prevent hallucinated land acquisition costs through strict input/output guardrails.

Resources and assets

Reference links and supporting material

Dataset notes

Synthetic dataset of commercial ground-up development opportunities with site metrics, zoning constraints, and submarket comps.

How this agent runs

Evaluates feasibility analysis correctness and checks that NeMo Guardrails block invalid financial metrics.

Challenge input

JSON containing land_cost, expected_gfa, target_rent_psf, hard_construction_cost

CrewAI

Framework assignment for multi-role agent collaboration.

NVIDIA NeMo Guardrails

Required AI engineering tool for constraining model responses.

Evaluated output

JSON with return_on_cost, dscr_projected, deal_approved boolean

Checks for
  • Verifies output cap rates are constrained between 2% and 15%
  • Accuracy of financial ratio calculations against ground truth math models • target: 0.95 • range: 0-1
Proof of success
  • Benchmark: Financial-Agent-Safety-Bench
  • Memo Accuracy Score target: 0.95
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • RAI · Required
  • CrewAI · Optional
Safety / Guardrails
  • NVIDIA NeMo Guardrails · Optional

Evaluation contract

  • guardrail_hallucination_block · Weight 1
  • memo_accuracy_score · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Development Underwriting Engine with CrewAI & NVIDIA NeMo Guardrails