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Privatization M&A Analysis Workflow with Mastra AI & Factory AI

Analyzing US-led investment consortiums prequalifying for Saudi sports privatisation requires strict financial valuation and legal rule validation. Build a TypeScript agent workflow using Mastra AI integrated with Factory AI autonomous codegen tools to automatically extract asset metrics, run cash flow models, and output investment risk scores. Ensure valuation precision within a 2% error margin.

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What you are building

Develop an automated M&A valuation agentic workflow for Saudi sports privatisation using Mastra AI and Factory AI tools.

How work is evaluated

Evaluation

Evaluates accuracy of financial cash flow modeling and regulatory compliance scoring generated by Mastra AI agent.

Datasets

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

How submissions are scored

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

Ownership Cap Verification

Flags compliance false if foreign equity exceeds 49% limit under Ministry regulations.

Binary check

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

Dimension 2

Valuation Precision

Measures variance between calculated DCF and ground truth DCF benchmark. • target: 0.98 • 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

  • Construct Mastra AI step-based workflows for financial analysis

  • Integrate Factory AI code generation primitives to execute dynamic DCF math

  • Validate Saudi ministry regulatory compliance rules programmatically

  • Output structured privatization bid evaluation reports

Resources

Dataset notes

Financial reports and regulatory ownership rules for 10 Saudi sports clubs undergoing privatization.

Challenge setup

Evaluates accuracy of financial cash flow modeling and regulatory compliance scoring generated by Mastra AI agent.

Challenge input

JSON object with revenue_history, discount_rate, ownership_structure_pct

Mastra AI

TypeScript framework requirement.

Factory AI

Used for dynamic financial modeling code execution.

Evaluated output

JSON object with dcf_valuation_usd, foreign_ownership_compliant, risk_score

Evaluation checks
  • Flags compliance false if foreign equity exceeds 49% limit under Ministry regulations.
  • Measures variance between calculated DCF and ground truth DCF benchmark. • target: 0.98 • range: 0-1
Configured evaluation evidence
  • Benchmark: FinAgent-Bench
  • Valuation Precision target: 0.98
  • 1 public reference case
Configured runtime
  • JavaScript execution harness
  • javascript sandbox (unavailable on Versalist)

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

View technical recipe

Configured tools

Action Space
  • Mastra AI · Required
  • Factory AI · Optional
  • Sacred · Optional
Orchestration
  • Mastra AI · Required

Evaluation contract

  • Ownership Cap Verification · Weight 1
  • Valuation Precision · Weight 1

Metrics

  • Valuation Precision · Target 0.98

Benchmarks

  • FinAgent-Bench
  • security

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON object with revenue_history, discount_rate, ownership_structure_pct

    Output: JSON object with dcf_valuation_usd, foreign_ownership_compliant, risk_score

    Execution harness: JavaScript

Evaluation tools

  • Mastra AI · Agent Orchestration Engine
  • Factory AI · Autonomous Code Generator

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Privatization M&A Analysis Workflow with Mastra AI & Factory AI