Build AI agents that actually get work done
We design and ship autonomous and semi-autonomous AI agents for operations, support, research, and product workflows. From tool selection and memory architecture to guardrails and observability, we handle the engineering so your agent is reliable in production, not just impressive in a demo.
From idea to autonomous workflow
A practical process that de-risks the agent early. We prove the behaviour first, then expand autonomy and integrations.
- 011–2 days
Scope & agent design
We define the agent's mission, inputs and outputs, the tools it needs, human-in-the-loop checkpoints, and the success metrics that prove it's working.
- 021–2 weeks
Build on the right platform
We prototype with a custom stack or a no-code/low-code platform based on your speed, control, and budget needs. The goal is a working agent you can test with real tasks.
- 032–4 weeks
Deploy with guardrails
We productionise the agent with evaluation harnesses, output guardrails, monitoring, fallback flows, and a clear path for continuous improvement.
Agent platforms we work with
We pick the stack that fits your needs — from fully custom code for control, to proven platforms for speed.
Custom code
LangChain, LlamaIndex, OpenAI Assistants, CrewAI, and bespoke Python/TypeScript backends for full control and scale.
Voiceflow
A leading no-code platform for conversational agents, voice, and chat experiences with fast iteration.
n8n
Self-hosted workflow automation with native AI nodes for building agents that connect your internal tools.
Make
Visual no-code automation with thousands of app integrations for quick proof-of-concept agents.
Botpress
Enterprise-grade chatbot and agent platform with strong multi-channel deployment options.
Relevance AI
Low-code platform for building an AI workforce with reusable tools, memory, and multi-agent teams.
CrewAI
Python framework for orchestrating multi-agent teams with role-based tasks and collaborative workflows.
Dify
Open-source LLM app development platform for building, operating, and improving AI agents and workflows.
Common AI agent use cases
Agents are most valuable where work is repetitive, data-heavy, and needs a little judgment.
Customer support agent
Answers tickets, searches your knowledge base, updates case status, and escalates complex issues to the right team.
Internal ops & research
Searches documents, drafts reports, summarises meetings, and prepares briefs so your team moves faster.
Sales / SDR assistant
Researches prospects, drafts personalised outreach, and prepares meeting notes so reps spend more time selling.
Document processing
Extracts data, classifies forms, checks compliance, and routes documents to the right people or systems.
Coding & QA agent
Generates tests, reviews pull requests, triages bugs, and suggests fixes to speed up engineering delivery.
Workflow automation
Triggers actions across tools, keeps humans in the loop, and handles exceptions without brittle if-this-then-that logic.
FAQs
A chatbot answers questions. An AI agent takes actions: it can call APIs, update databases, plan multi-step tasks, handle exceptions, and decide when to escalate to a human. Agents are built around a goal, not just a conversation.
A focused agent prototype is typically ready in 1–2 weeks. Production-ready agents with full guardrails, integrations, and observability usually ship in 4–8 weeks, depending on complexity.
Both. We choose the stack that matches your speed, control, and budget needs. We often start on a no-code or low-code platform to prove value fast, then move to custom code when you need scale, deeper integrations, or unique reasoning logic.
We build evaluation harnesses, output guardrails, human-in-the-loop checkpoints, and observability dashboards. Agents only get more autonomy after they prove reliability against real tasks and edge cases.
Yes. We connect agents to your CRM, helpdesk, databases, internal APIs, and knowledge bases using secure integrations. Most of the value comes from fitting the agent into your existing workflow.
We staff blended teams from $3,300 per week. The total cost depends on agent complexity, number of integrations, and how much autonomy you need. We scope everything clearly before work starts.
Book a call with Naresh
A 30‑minute discovery call with our founder. Walk through your idea, audit the fit, and leave with a clear next step, no pitch, no pressure.