Domain products
PracharVedam, Axaria, ShikshaVedam focus on specific business work. Each has its own audience, workflow and product experience.
Meet the productsThe company behind the products
DataVedam is an AI product and engineering company. We work across business applications, agent frameworks and model technology—connecting the experience people see with the systems that make it useful.

A growth team needs its brand context to travel from brief to creative. A caller needs a conversation that leads somewhere. A school needs operational information to reach the people responsible for it.
Those worlds have different workflows and expectations. Our products are built around those differences: PracharVedam for marketing and growth, Axaria for voice agents, and ShikshaVedam for school operations.
Underneath, the engineering questions connect. How does the system know its context? Which actions are allowed? What needs human review? How does a team understand what ran? Sarva and Bodhi address agent governance and model development as technology in their own right.
We also work with teams whose requirements need a dedicated implementation. The starting point is the workflow and its constraints, followed by an experience, an architecture and an agreed way to evaluate the result.
Products to work with. Technology to build with. Engineering to make it fit.
PracharVedam, Axaria, ShikshaVedam focus on specific business work. Each has its own audience, workflow and product experience.
Meet the productsSarva provides governed product-agent hosting and execution boundaries. BodhiVedam supports the path from teacher-model learning to evaluated student artifacts.
Explore the technologyAgent-native experiences, private AI workflows and system integration are shaped around the customer’s context. Scope starts with the task and its data, authority and deployment constraints.
How we buildAgentDLC helps teams work with coding agents through practical workshops and a controlled development lifecycle. Learning connects to implementation, review and evidence in a real engineering task.
Explore AgentDLCIntelligence becomes useful when the whole experience is considered.
A campaign. A school day. A conversation. We start with the people and the task, then decide where intelligence belongs.
The model is one part of the product. Language, interaction, permissions, integration and operations shape whether it is actually useful.
Useful automation needs appropriate boundaries. People should understand the decisions that matter and retain control where it counts.
A compelling demonstration starts a conversation. An observed outcome earns confidence. We keep those two things distinct.
Building a useful product calls for several kinds of expertise. We work at their intersections, where a good idea becomes an experience people can actually use.
A campaign needs brand consistency and a clear path from idea to approved creative. A voice conversation needs timely information, a bounded action and a useful handoff. A school workflow needs role-specific records and the right review before information is published.
Those differences are why we build focused products rather than treating every business as the same chat interface. The shared disciplines—experience design, information modelling, integration and evaluation—also help us approach a new customer problem without assuming that an existing product is the answer.
Our website separates products, services and technology so you can find the right starting point. A product page explains a particular application. A service page describes work we can scope with your team. A technology page explains a building block and how to evaluate it.
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Bring us the work that matters.
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