Generative and agentic AI products
Digital twins of customers, assets and processes; agentic productivity tools; cost-optimisation systems; and platforms that move core business metrics rather than report them.
See productsUnderstand deeply,then act responsibly.
Twyngentic develops, licenses and supports next-generation AI and data software, and provides the professional services that bring it to life, in India and internationally.
TWYNGENTIC
01 — Why we exist
Dashboards, reports and alerts have become very good at telling people what went wrong. We exist to close the gap to doing something about it.
Every insight still needs someone to open a ticket, draft the memo, chase the missing document or reconcile the mismatched field by hand. Not by making software better at describing work, but by making it capable of doing the work, under the same governance a regulator, an auditor or a board would expect from a trained employee.
02 — What we do
Products, platforms and the people to run them.
Three lines of business, one reference architecture underneath.
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Data governance and management products
Data quality, master and reference data, catalogs, business glossaries, lineage, reconciliation, integration and natural-language BI, built as products in their own right.
See the platform03
Global technology services
Research and development, systems integration, customisation, technical support and training wrapped around every product we sell, for clients in domestic and international markets.
See services03 — How we work
The same method, wealth client or paddy field.
Six working principles that every engagement, product and agent follows.
Twin first
Prove it on a twin
We never recommend, draft or act on live production data until the approach has been proven on a synthetic, permissioned twin.
Agentic, not automated
Reasoning, with limits
Automation follows a fixed script. Our agents reason over context, and every agent's authority ends exactly where a person's judgement is legally or commercially required.
Governed by design
Controls from day one
Corroboration thresholds, confidence scores, evidence citation and audit trails are how the system is built from day one, not features added later.
Built once
Reused everywhere
A single reference architecture of governance, AI core, semantic and data layers underpins every product family.
Evidence over adjectives
Numbers we can trace
Every claim we make about an outcome is a number we can trace to a source, not a marketing estimate.
People at the centre
Farmer, customer, subscriber
We measure success by what changes for the person at the end of the chain, not by how many models we deploy.
04 — Responsible AI
Five controls. Every deployment.
Deployments can run on-premises, air-gapped or in a dedicated sovereign cloud, with zero data retention on foundation models and role-based access that mirrors your organisation.
| Control | What it means in practice |
|---|---|
| Consent by design | Only permissioned data is used, and internal, open-banking, ecosystem and public signals are kept clearly separate. |
| Suitability first | Recommendations are gated by risk appetite, vulnerability and advice rules before anyone sees them. |
| Explainable outputs | Every recommendation shows why a signal was prioritised and which evidence it used. |
| Human approval | Regulated advice, financial decisions and citizen entitlements always route through a named approver. |
| Closed-loop learning | Outcomes are captured to refine propensity, engagement and next-best-action logic over time. |
Power to act