Fomogo positions itself as an AI hiring platform but the tech stack reveals a deeper play: heavy investment in data pipelines (Airflow, Dagster, Temporal, Prefect), document processing (pdfplumber), and vector search (pgvector, Pinecone) alongside recruiting-focused tools (HubSpot, Apollo, ZoomInfo). The project list shows parallel tracks in resume/document screening and financial-data extraction from SEC/BSE filings—suggesting the core product is an AI screening engine with embedded data infrastructure. Early-stage hiring is concentrated in data and engineering (4 of 7 roles), reflecting infrastructure debt rather than sales-led growth.
Fomogo is an AI-powered recruitment platform targeting startups, SMBs, and staffing agencies. The product surfaces AI-driven resume screening, asynchronous video interviews, candidate scoring, and ATS integrations. It also serves job seekers with interview prep and resume optimization. Founded in 2024, the Bengaluru-based company is a 2–10 person team actively hiring across product, engineering, sales, and marketing roles. The heavy lift in data-ingestion pipelines and document parsing suggests the platform relies on proprietary datasets and processing layers to power its screening and scoring capabilities.
Fomogo uses Azure, AWS, GCP for cloud infrastructure; Python and SQL for backend; Apache Airflow, Dagster, Temporal, and Prefect for data pipelines; Pinecone and pgvector for vector search; pdfplumber for document parsing; and HubSpot, Apollo, ZoomInfo for sales intelligence integrations.
Core projects include batch and real-time data pipelines for document corpora, PDF and financial-data extraction from investor presentations and BSE/NSE filings, retrieval-ready datasets for RAG, and monthly software releases with reliability improvements.
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