Siddhrans InfoTech builds AI agents, copilots and intelligent applications, the enterprise software and data beneath them, and the embedded systems that take the same intelligence into machines.
Agents, copilots and automation connected to your data, your systems and your people, with humans in the loop where judgement matters.
Concept interface · invented sample data, not a Siddhrans deployment
Role-specific assistants and multi-agent solutions that work from your documents and systems, cite their sources and wait for a person to approve what matters.
Concept interface · invented sample data, not a Siddhrans deployment
Intelligent document processing and enterprise knowledge retrieval: extract fields, point to the page they came from, and flag what a person should check.
Concept interface · illustrative overlay on a licensed stock photograph, not an inspection record
Detect, locate and check features on the line, with a clear pass, flag or review outcome and a person making the final call.
Concept interface · invented sample data, not a Siddhrans deployment
Predictive analytics and machine learning in the cloud or close to the sensor, with an explanation of why something was flagged and what to do about it.
Concept interface · sample data
Generative AI applications for business tasks, built into the web and mobile software your people already use.
Fifteen named systems built since 2016: full-stack, database-backed and workflow-driven. They are the platform foundation we bring AI into.
15 systems · choose one
Concept interface with placeholder data, not a screenshot of a delivered product
A structured way to run programmes, deliver content, assess learners and process results, in one platform instead of spreadsheets, email and paper.
One team engineers the sensor, the firmware, the model and the decision, so intelligence does not stop at the dashboard.
Current, vibration, temperature, optical and pulse sensors.
ESP32 and Arduino-class firmware: drivers, signal processing, local control.
Pattern analysis and deviation detection, validated with domain engineers.
Rules and models turn readings into a state: normal, watch or act.
Alerts, audit logs and automated follow-through.
Steps 3 to 5 are concept visuals with illustrative sample data (pump P-204). Steps 1 and 2 are prototype images supplied by Siddhrans.
Detect abnormal motor load earlier and guide maintenance.
Representative illustration · Monitoring architecture.
Boards, firmware and prototypes for devices that sense and decide.
Intelligence is only as dependable as what it runs on. These four layers sit under every pillar.
A workflow, a pile of documents, a production line, a device. Describe it and we will tell you how we would approach it.
How we label our work: systems built, engineering capability and more.
