Engineering for the AI data era
LangData AI helps governments and enterprises upgrade critical digital platforms with scalable architecture, voice-first accessibility, document intelligence, and AI systems that improve trust at national scale.
Digital India, Next Phase
As India’s digital ecosystem matures, citizens expect public platforms to match the speed, reliability, and intelligence of the private-sector apps they use every day.
LangData proposes a reliability-first, AI-forward partnership model for critical government applications: stabilize the architecture, simplify the user experience, and apply AI where it improves service delivery.
About LangData AI
LangData AI connects Silicon Valley engineering standards with the resilience and practical urgency of Indian entrepreneurship. We build critical platforms that are faster, more accessible, and ready for AI citizens and operators can trust.
Co-Founder
Seasoned software architect and three-time entrepreneur with over a decade of experience building high-scale distributed systems. Sourav has served as the first engineer at Y Combinator startups and led engineering teams scaling products past 1M users and $1M+ ARR.
Co-Founder
Chartered Accountant, Certified Information Systems Auditor, and business structuring leader with 14+ years across finance, compliance, corporate governance, multi-jurisdiction setup, and operational controls.
Enterprise teams we can support
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Four Practices
Strategy, data foundations, AI products, and analytics need to stay connected. That is the operating model.
Find the AI work worth shipping, then define the data, risk, and delivery path behind it.
Build the pipelines, warehouses, lakehouses, and quality checks that make AI and analytics reliable.
Move copilots, RAG systems, and agent workflows from prototype demos into owned production systems.
Replace fragmented reporting with governed metrics, usable dashboards, and decision systems teams trust.
Core Challenge
Critical applications can crash or degrade during scheme rollouts, exam results, payment windows, or sudden public demand.
Interfaces that work for trained operators often fail citizens who need simple, multilingual, mobile-first service flows.
Backlogs of forms, documents, tickets, images, and records slow down verification, routing, and service delivery.
Solution
Re-architect core workflows with distributed systems, durable jobs, Go services, containers, observability, and load-tested release paths.
Target: low-latency citizen experiences during peak traffic.
Use AI for accessibility, verification, routing, summarization, and decision support rather than novelty demos.
Target: faster processing, clearer communication, and higher citizen confidence.
What We Can Do
Engagement Model
Each engagement is structured around shippable product increments, not loose advisory work. We define the workflow, build the first product surface, harden it for real users, then expand it with measurable controls.
Turn a broad modernization goal into a ranked product backlog with user journeys, data sources, risk points, and success metrics.
Inspect the current platform like a product acquisition: architecture, uptime risks, data quality, security posture, and integration seams.
Build a working vertical slice around one high-value workflow, with real content, real forms, real documents, and measurable operator feedback.
Harden the prototype into a deployable product with authentication, observability, queues, human review, data governance, and release controls.
Add the control plane leaders need: dashboards, SLAs, escalation paths, model monitoring, analytics, and continuous improvement cycles.
Expand from one workflow to departments, regions, languages, and channels with a governed roadmap and repeatable implementation playbook.
Stack
Contact
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