Enterprise AI Platforms
We build scalable AI products, agentic platforms, enterprise applications and voice-enabled systems for businesses in India — on Google Cloud and AWS, alongside Smriti's own voice models and AI harnesses.
What it means
Businesses in India are not short of access to AI models. What they need is a system that works with their own knowledge and software, fits the way their teams already work, and keeps a person accountable where a decision matters.
An enterprise AI platform is that system. We design and engineer it end to end: the product people use, the agents and workflow behind it, the connections to approved data and tools, and the evaluation and operations that keep it dependable. We are not reselling access to model APIs.
Anatomy
Where people make requests, review proposed work and see outcomes.
Application logic that divides a task between specialised agents and workflow steps, shares context between them and calls tools under defined rules.
Gemini models, foundation models available through Amazon Bedrock, or Smriti-developed models such as our voice models — chosen for the task.
Documents, records and business systems, reached only within the permissions each user holds.
Actions that change records, send messages or commit resources pause for a person, who approves, edits or sends them back. Each decision is recorded.
Before release — task-level test sets agreed with the business.
In use — monitoring, traces and review of real outcomes.
Over time — evidence that decides the next change.
Cloud foundations
Google Cloud
Agentic products and enterprise platforms that combine Gemini models, Gemini Enterprise integrations, the Agent Development Kit and Google speech technologies with our own application engineering.
Technologies we build with
AWS
Business platforms that combine foundation models available through Amazon Bedrock with an organisation's knowledge, tools and workflows — with the product and systems engineering done by us.
Technologies we build with
Supporting services such as Amazon Bedrock Knowledge Bases, Guardrails or AgentCore are used only where a project requires them.
Google Cloud and AWS provide models and managed services. The product, the integrations and the engineering around them are Smriti's work.
Our own engineering
Voice AI
Developed by SmritiOur own voice models, refined and evaluated for the application they serve, with the speech application engineering around them. Third-party speech services are integrated where they are the better fit.
AI Harnesses
Developed by SmritiThe engineering around a model that decides what it sees, what it may do and how its work is checked — for third-party or Smriti-developed models, chosen per task.
The line between what we develop and what we build with is stated plainly — here, and in each project write-up.
What we build
Coordinated agents that retrieve information, reason over it and take defined steps across business systems — with a person approving the steps that matter.
Applications with AI built into the work itself: knowledge assistants grounded in approved sources, document and case handling, and model-assisted steps inside existing processes.
Services people can speak to, combining our own voice models or integrated speech services with dialogue, business logic and hand-off to a person.
Capability overviews in the portfolio
A capability overview describes what we engineer in this kind of project. It is not a case study: it names no customers and claims no results.
How we engage
The users, the decision or task, the systems involved and what a good outcome looks like.
Interfaces, workflow, model choices, data access and the points where a person stays in control.
Application engineering and integrations. Models are adapted only when the task requires it.
Task-specific tests and measurements, including where the system falls short.
Into the environment it must run in, with the monitoring needed to operate it.
Evidence from real use feeds the next iteration.
Improvement feeds back into understanding — the process is a loop, not a hand-off.
Enterprise AI Platforms