Data and AI strategy
Maturity assessments, value cases for each use case, regulatory alignment, and a data governance operating model with clear owners, stewards and councils.
Software alone does not transform an enterprise; the people who implement, integrate and run it do. We wrap end-to-end services around every product we sell.
Agile iterations across four workstreams: governance framework, platform and integration, metadata, and data quality.
Maturity assessments, value cases for each use case, regulatory alignment, and a data governance operating model with clear owners, stewards and councils.
Policies, catalog, glossary, lineage, data quality, MDM and RDM, delivered on TwynTrust or on the governance platform you already own.
Taxonomy workshops, twin builds, agent design, retrieval grounding, evaluation and guardrails, with a working twin in weeks rather than months.
Connectors to core banking, OSS and BSS, ERP, CRM, state data centres and digital public infrastructure.
Data stewardship as a service, data quality operations, agent and model operations, cost tracking and SLA-based technical support.
Data literacy for leaders, steward certification, and vernacular onboarding for field teams across district and block levels.
Joint R&D and sandbox pilots on synthetic twins, so you can test a new idea without touching live data.
NOC maturity assessments, assurance architecture, and AIOps and agent rollout from reactive to autonomous operations, plus managed NOC support with agents handling first-line triage.
Responsible, accountable and consulted — agreed before the first data contract is signed.
| Activity | Producer | Consumer | Governance |
|---|---|---|---|
| Define the contract | Responsible | Consulted | Accountable |
| Approve the contract | Consulted | Consulted | Accountable |
| Monitor quality | Responsible | Responsible | Consulted |
| Change the schema | Responsible | Consulted | Accountable |
| Manage SLAs | Responsible | Responsible | Consulted |