AI Agent Development & Automation
Give repeatable work a capable, accountable digital teammate
We design agents that understand business context, use approved tools, retrieve the right knowledge, perform actions and hand work to people when judgment is required.
What is an AI agent in a business workflow?
An AI agent is software that owns a defined piece of work: it reads context, retrieves approved knowledge, uses permitted tools to act, and hands off to a person when a decision needs human judgment. It is a digital operator, not a chatbot.
Based in Bengaluru, working with companies across India and abroad.
What the engagement produces
Concrete deliverables, agreed in writing before work starts. You keep every one of them.
- Agent boundaries
- Tool integration
- Retrieval and knowledge configuration
- Permissions
- Evaluation plan
- Logging
- Human escalation
- Deployment and monitoring
The same work, redesigned
Pick an example. See how the work moves today, and how the new system runs it: who does each step, and how long it takes.
- Rep reads every enquiryqueue 1 day
- Looks up the account20 min
- Decides if it's worth a call
- Books a meeting2 days
- Agent reads the enquiryAgent
- Checks CRM and qualifiesAgent
- Proposes two meeting slotsAgent
- Rep approves the bookingPerson
Illustrative scenario. Every engagement starts from your real process.
How we approach it
- Types of agentsAgents are shaped by the work they own. Sales agents · Customer-service agents · Knowledge agents · Operations agents · Voice agents · Document intelligence
- Permission modelTools are allow-listed and enforced in code, not in a prompt. Reading is unrestricted; writing user data needs an explicit interaction; external actions such as sending email or booking need explicit confirmation. High-impact actions stay with people.
- Knowledge modelAgents retrieve from approved, versioned sources with metadata for freshness and visibility. Company-specific facts come from authoritative content, and an agent says it does not know rather than inventing.
- Human handoffEvery agent has a defined route to a person, carrying the context gathered so far, with consent, so nobody starts over.
- Voice agentsLow-latency voice with interruption handling, live transcripts and the same knowledge and tool policy as text. Voice is always opt-in.
- ObservabilityTool calls, failures, latency and cost are logged and measured. Agents are evaluated against test sets covering accuracy, safety and tool correctness before and after deployment.
From the first question to working software
One integrated team of product managers, engineers, AI specialists, designers and QA.
We study the problem with the people who live it: workflow, customers, constraints.
Problem brief agreedWe agree what success means, what is in scope and the hypothesis we are testing.
Scope signed offFlows, interfaces and architecture, tested as a prototype before engineering starts.
Prototype approvedWorking software and artefacts, demonstrated every week.
Features acceptedRelease to real users with documentation, monitoring and a runbook.
Release acceptedWe measure what happened and turn it into the next roadmap.
Roadmap reviewedWhere teams start
- AI lead qualificationEvery enquiry captured, qualified and routed with context, in minutes rather than days.
- AI customer support agentRoutine questions answered from approved knowledge; complex cases handed over with the full thread.
- AI voice agentCalls answered, requests captured and slots booked, with a transcript for every conversation.
- AI document processingFields extracted with citations, uncertain items flagged, and a reviewer in control.
- AI knowledge assistantAnswers from your own documents and policies, with sources and access controls.
Questions buyers ask
What is an AI agent in a business workflow?
An AI agent is software that owns a defined piece of work: it reads context, retrieves approved knowledge, uses permitted tools to act, and hands off to a person when a decision needs human judgment. It is a digital operator, not a chatbot.
Do we need to know what to build first?
No. We start with a short discovery of how the work happens today, then recommend what to build, or what not to.
What does it cost?
Scope and price are confirmed in writing after discovery. We don't quote from a feature list.
Related insights
- What is an AI-native company?An AI-native company redesigns workflows, decisions, data access and software so AI is part of how the business runs. What it means, how it differs from adding AI tools, and how to start.
- What should an AI agent be allowed to do? A practical modelA practical permission model for AI agents: four levels of action from read-only to high-impact, how to enforce them in code rather than prompts, and how to design the handoff to people.
- The anatomy of a production AI agentKnowledge, tools, permissions, a provider abstraction, evaluation and observability: the parts that turn an AI demo into a production AI agent a business can rely on.
Ready to explore an ai agent?
Describe the problem in your own words. A person replies with a suggested first step.