New October Industrial Complex Financing Agent
ADCB Egypt and IDG's $12m financing deal for New October industrial park requires tracking tenant leasing milestone disbursements. Build a stateful automated workflow in Python using FastAPI and PostgreSQL to evaluate tenant lease terms and trigger bank loan drawdowns. Ensure zero unauthorized disbursement executions across test lease submittals.
What you are building
Build an automated loan drawdown workflow for industrial complexes using FastAPI and PostgreSQL.
How work is evaluated
Evaluates loan drawdown authorization logic against industrial tenant lease parameters.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
Condition Precedent Check
Fails if approved is true when lease_signed is false or completion_pct < 50.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Disbursement Accuracy Rate
Percentage of valid drawdown requests correctly authorized without errors. • target: 1 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Design transactional database schemas in PostgreSQL for industrial facility financing
Build FastAPI endpoints for processing tenant lease agreements and site progress milestones
Enforce compliance rules before issuing tranche disbursement instructions
Audit all loan drawdowns with immutable transaction logging
Resources
New October industrial city lease contracts and construction phase progress data.
Challenge setup
Evaluates loan drawdown authorization logic against industrial tenant lease parameters.
Challenge input
JSON object with complex_id, tenant_lease_signed, completion_pct, requested_drawdown_egp
FastAPI
Standard Python microservice development framework.
Evaluated output
JSON object with approved, tranche_amount_egp, rejection_reason
- Fails if approved is true when lease_signed is false or completion_pct < 50.
- Percentage of valid drawdown requests correctly authorized without errors. • target: 1 • range: 0-1
- Benchmark: FinAPI-Bench
- Disbursement Accuracy Rate target: 100%
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
- Zed · Required
- ElevenLabs · Optional
- Traceloop · Optional
Evaluation contract
- Condition Precedent Check · Weight 1
- Disbursement Accuracy Rate · Weight 1
Metrics
- Disbursement Accuracy Rate · Target 1
Benchmarks
- FinAPI-Bench
- security
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON object with complex_id, tenant_lease_signed, completion_pct, requested_drawdown_egp
Output: JSON object with approved, tranche_amount_egp, rejection_reason
Execution harness: Python
Evaluation tools
- FastAPI · Web Framework
Recipe freeze marker
No recipe freeze time is recorded.