SMS and messaging platform with ML-driven campaign targeting
Bhash runs a global SMS delivery platform connecting backend systems to mobile phones, now scaling toward AI-powered campaign optimization. The tech stack reveals a data-heavy operation: Python, Kafka, Airflow, and ML libraries (scikit-learn, PySpark) power data pipelines, enrichment, and a new AI targeting engine. The project list—forecasting models, campaign effectiveness scoring, and number intelligence graphs—shows a shift from basic SMS relay toward performance analytics and revenue optimization. Hiring is accelerating across data (2 open), sales (2), and product roles, indicating aggressive growth in both product capability and sales execution.
Bhash provides carrier-grade SMS and mobile messaging services, connecting corporate backend systems to GSM/CDMA handsets across India and globally. The platform operates as a hosted service with plug-and-play licensing, built through partnerships with mobile operators. Core customers range from corporates to startups seeking SMS-based communication and messaging solutions. Internally, the company is managing three operational challenges: scaling data infrastructure to handle high-volume messaging, improving campaign ROI through targeting, and maintaining platform reliability as throughput increases. The current focus on data pipelines, enrichment, and ML-driven campaign scoring reflects a business model transition from connectivity provider to data-informed messaging platform.
Python, Kafka, Apache Airflow, FastAPI, PySpark, scikit-learn, AWS, GCP, SQL, and WhatsApp API. The stack emphasizes data processing (Pandas, NumPy, Scrapy) and infrastructure for high-volume messaging and analytics.
Data pipelines, ML-driven campaign targeting, forecasting models, campaign effectiveness scoring, and a number intelligence graph. Projects also include hiring dashboards and cash reserve planning, reflecting growth and operational scaling.
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