We automate the repetitive manual work that eats your team’s time.

We automate repetitive, time-consuming manual work with AI, in any business or industry. We learn how the work really runs, map where AI pays, then build and run production AI systems that your team owns. We also run two ready-made systems that came out of that work: Harnad Voice for phone calls and Harnad Connect for WhatsApp.

With an AI automation audit. We sit with the people who do the work, map the process, and rank each repetitive task by time saved and cost to automate. You get a process map, a ranked list of opportunities, and a cost and savings estimate, and we agree in writing on the one worth building first.

We start by sitting with the people who do the work and mapping the process. Then we rank each repetitive task by the time it takes, how often it happens, and what it costs to automate, and build the one with the clearest payback first. If AI is not the right answer for a task, we say so.

Yes. Many of the most repetitive tasks start on paper, in chat threads, or on a phone call. We have built voice reporting for field teams, where people speak a report and AI turns it into a structured record, and we can digitise forms, inspections, and records as part of the build. Where a step needs a person on site, the system supports them rather than replacing them.

No. We target the repetitive, time-consuming tasks that fill people’s days: copying data between systems, chasing documents, answering the same questions, compiling reports. Your team keeps the work that needs judgement, relationships, and exceptions, and every system we build has checkpoints where a person approves or takes over.

It depends on the process, so we quote a fixed scope after the audit rather than guessing up front. Most builds in our case studies took four to eight weeks. To keep running costs low we use the right model for each task, cache and route requests, and measure the cost per process, so you can see what each automated task costs to run.

Most processes need one well-built AI system. When a process has several distinct stages that need different skills, for example researching, drafting, checking, and approving, we use several specialised agents coordinated by an orchestrator. We use that design only when the process needs it, because simpler systems cost less to run and are easier to maintain.

Most of the projects in our case studies went from kickoff to production in four to eight weeks. You will see working software in the first sprint, and the milestone plan is agreed in writing before we start building.

You do. We deploy into your cloud accounts, hand over the source code, prompts, and documentation, and you keep full ownership of the IP and the data.

Consent capture, transcripts, access control, and isolated tenancy are built in. We keep data in your own cloud where required, do not use your data to train models, and are happy to work under NDA. Our security page lists where data lives and which providers we use.

We are cloud-native on Google Cloud (Cloud Run, Vertex AI, AlloyDB, BigQuery, Firestore) and build with Next.js, TypeScript, and PostgreSQL. For voice and messaging we work with Twilio, ElevenLabs, and the official WhatsApp Business Platform. We integrate with the tools you already use.

Yes. We are headquartered in Chennai and deliver worldwide, with working-hour overlap for teams across time zones.