Telcos sit on the richest behavioural dataset in the country and the thinnest margins. AI is the only lever that fixes both at once.

Where we work

National and regional telcos, ISPs, hyperscale and managed-service platforms, large SaaS operators, and the engineering organisations inside global product companies running platforms at India scale. We work both on the network side and the engineering-productivity side.

Where AI changes the economics

• Network operations. Multi-vendor RAN optimisation, energy steering, anomaly detection across NMS/EMS feeds, and incident triage that reads its own dashboards before paging a human.
• Customer care in vernacular. Speech recognition tuned for Indian English, Hindi, and major Indic languages; agent-assist that grounds responses in product policy, network state, and customer history.
• AIOps for SaaS and platform engineering. Log RCA, alert correlation, on-call summarisation, runbook automation. The work that consumes SRE capacity in any large platform.
• Code copilots and engineering productivity. Repository-aware copilots with internal coding standards, security policies, and architectural constraints baked into the prompt and the evals.
• B2B sales and account-management copilots. Account intelligence over CRM, billing, ticketing, and usage telemetry — surfaced to AMs as next-best-action, not yet another dashboard.

What we will not do

Touch lawful-interception infrastructure. Train on customer payload data without explicit licence-condition compliance. Replace your SRE on-call with an agent that cannot explain its own action.

What you get

Network and engineering AI integrated with the systems you already run — NMS, EMS, billing, CRM, observability — and deployed inside your data-residency, IAM, and CERT-In incident-response perimeter. Operational metrics move; the system tells you which interventions actually moved them.