ShepHertz Technologies launched AgentAnywhere, a sovereign agentic AI platform that lets banks, insurers, hospitals, governments and the BPOs that serve them run AI agents entirely inside their own infrastructure, on their cloud, in their jurisdiction, and under their own encryption keys. Announced on India’s Independence Day, the platform pairs a family of models trained in India with a governance layer that masks personal data before any model sees it, screens every request for prompt injection, and closes each call with a signed, auditable record.
The timing is deliberate. India built its own space programme, its own payments rail and its own vaccines; ShepHertz argues it should not have to rent its intelligence. Most enterprises deploying agentic AI send their most sensitive information, customer records, source code, medical files, transaction histories, outside their own boundary to a model they do not control, in a jurisdiction they did not choose. For a consumer app, that is a trade-off; for a bank under RBI supervision, a hospital handling patient data, or a government department, it is a governance risk waiting to be audited.
AgentAnywhere is built for institutions that are no longer asking whether to deploy agentic AI, but how to do so in environments where a hallucination can become a regulatory event, where an agent’s autonomy must map to a human accountability chain, and where every decision has to be audit-ready. The platform’s sovereignty is architectural rather than an add-on: models, agents and governance all run inside the customer’s cloud, region-pinned or fully air-gapped, rather than sovereignty being offered as a late-stage deployment checkbox.
At the core is an enforced trust layer that, ShepHertz stresses, is fully operational rather than a planned feature. Veil masks and de-identifies personal, financial and regulated data before it reaches any model, logging every mask. Kavach acts as an inline security shield, screening each request and response for prompt injection and jailbreaks and returning a verdict, allow, block or flag, to an append-only log. An Agent Universal Gateway governs every model call, tool call and agent-to-agent message from a single control point, while Custodian maps the platform to SOC 2, ISO 27001, and RBI controls and ships signed evidence packs continuously. Nothing leaves the pipeline without a signed Trust Receipt recording what was masked, what was screened, which model ran, and under which policy.
AgentAnywhere is underpinned by seven model families, all trained in India and all served behind the same governance layer, each named in Sanskrit. Taksha, its sovereign AI-engineering and coding model, is generally available. Six further families follow through 2026: Manthan for general reasoning, Kuber for BFSI, Seva for service operations, Tatva for on-device and edge deployments, Astra for defence, and Sanjaya for critical telemetry, with Astra and Sanjaya offered on a partner-scoped basis. Each family ships in Fast, Pro and Max tiers, all running inside the customer’s VPC under one governance surface, and each arrives only after passing an execution-graded testing battery, a bar that saw two candidate models rejected for failing the gates, with the failures published alongside the results.
Complementing the core families, ShepHertz is developing Manthan Vaani, an Indic-language line. Customers can also bring their own open models, including Mistral, Qwen, GLM, Gemma, GPT-OSS and Llama, running them inside the same perimeter and under the same governance, each carrying provenance. Underpinning training is Shuddhi, ShepHertz’s sovereign data factory, which cleanses training corpora and issues build manifests that every training run cites.
ShepHertz also notes that it runs its own operations on the platform, from marketing lead generation and enterprise RFP responses to contract review and cloud cost optimisation, making the company its own first production customer.
Marking the launch, Siddhartha Chandurkar, CEO, ShepHertz Technologies, said, “Enterprises in regulated sectors aren’t debating whether to adopt agentic AI anymore; they’re grappling with how to do it without their most sensitive data leaving their control. AgentAnywhere was built to close that gap. Sovereignty here isn’t a feature we bolt on at the end; it’s the architecture. The models are Indian-built, the governance runs inside the customer’s own perimeter, and every single call is masked, screened and signed. Choosing Independence Day to launch is our way of saying technological self-reliance should extend to intelligence itself.”