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Cost-Constrained Multi-Agent Orchestration for Business Intelligence in Emerging Markets

Faculty-advised research — team forming

→ Core contributors included as co-authors

Business Intelligence AI

Cost-constrained intelligence for operators in emerging markets where incumbent analytics tooling is priced out of reach. The analytical access gap is the organizing constraint. Research conducted with active deployment evaluation across geographic regions.

Multi-AgentAWSMCPCost OptimizationAgent OrchestrationBusiness Intelligence

The crisis

  • Small businesses in tier 2/3 cities make high-stakes decisions on intuition analytical tools cost $5K–$50K/year
  • India: 63 million MSMEs, the majority with zero access to data intelligence tools
  • Africa: small businesses are the economic backbone of entire countries but have no access to market intelligence
  • The digital divide is not only internet access it is access to intelligence tools incumbents price at enterprise rates
  • The analytical gap compounds over time: businesses without data lose to businesses with data, regardless of product quality

About this research

Business intelligence tooling assumes enterprise budgets and procurement cycles. That creates a structural gap: operators in emerging markets make high-stakes decisions without analytical support. This thread studies that constraint across deployment environments with constrained cost parameters.

Key findings

  • (In Progress)

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Open roles

Backend Engineer

Open

Build cost instrumentation and benchmarking infrastructure. Extend agent architecture to additional market verticals. Optimize caching and context management layers.

Skills: Python, AWS, MCP, Cost Profiling, System Design

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Data Scientist

Open

Design evaluation framework for analytical output quality. Run statistical analysis across deployment regions. Support academic writing and results interpretation.

Skills: Statistics, Python, Evaluation Design, Data Analysis, Academic Writing

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