AI Agent Development That Automates Real Work – KenStack Technologies

AI Agent Development That Automates Real Work

Singapore · UK · Worldwide

AI Agent Development That Automates Real Work for global teams.

Custom AI agents that read, decide and act inside your CRM, inbox and business tools, with a person approving anything that matters.

KenStack is an AI agent development company that builds agents for real business tasks: qualifying leads, answering and resolving support tickets, updating records, preparing quotes and chasing follow-ups. An AI agent goes further than a chatbot. It does not only answer questions, it takes actions in your systems through secure APIs, following rules you set.

Every agent starts from one workflow and one measurable result, such as hours saved per week or response time. We map the steps, the systems involved and the points where a person must approve, then build a working pilot on your real data before connecting it to production tools.

Agents are built with large language models such as OpenAI GPT and Claude or open-source models, orchestration frameworks such as LangChain and LangGraph, and workflow tools such as n8n. Each one includes permissions, action logs, cost tracking and human hand-off, so you can see exactly what the agent did and why. You own the code, prompts and configuration.

What We Build

What we build with AI agents.

Typical projects we deliver, each scoped around a measurable business result.

  • Customer support agents by KenStack Technologies

    Customer support agents

    Resolve common tickets end to end, look up orders and policies, and escalate the rest with a full summary.

  • Sales & lead qualification agents by KenStack Technologies

    Sales & lead qualification agents

    Research inbound leads, score them, update the CRM and book meetings with the right salesperson.

  • Inbox & back-office agents by KenStack Technologies

    Inbox & back-office agents

    Read emails and attachments, extract the details and create invoices, orders or tasks in your systems.

  • Internal knowledge agents by KenStack Technologies

    Internal knowledge agents

    Answer staff questions from SOPs and policies, then take the next step, such as raising a request.

  • Reporting & operations agents by KenStack Technologies

    Reporting & operations agents

    Pull data from several tools, prepare weekly reports and flag exceptions for a manager to review.

  • Multi-agent workflows by KenStack Technologies

    Multi-agent workflows

    Several specialised agents that hand work to each other for longer processes, with checkpoints in between.

How We Work

From discovery to production in four steps.

  1. 01

    Discovery

    A free call and short audit to understand goals, users, data and constraints, ending in a clear scope and quote.

  2. 02

    Design & architecture

    Wireframes, data model and technical plan reviewed with you before development starts.

  3. 03

    Build in sprints

    Development in one to two week sprints with a working demo and your feedback each time.

  4. 04

    Launch & support

    Testing, deployment, training and a warranty period, then optional monthly support.

FAQ

AI Agent Development That Automates Real Work: common questions

What is the difference between an AI agent and a chatbot?

A chatbot answers questions in a conversation. An AI agent can also take actions: it reads data from your systems, makes a decision based on your rules and then updates records, sends messages or creates tasks. Many projects start as a chatbot and add agent actions once the answers are reliable.

Which tools can your AI agents connect to?

Any system with an API or a supported integration, including CRMs such as HubSpot and Salesforce, Gmail and Outlook, Slack and Microsoft Teams, WhatsApp Business, Shopify, accounting tools and your own databases.

How do you stop an AI agent from making costly mistakes?

Agents only get the permissions they need, actions above a set value or risk need a person to approve them, and every step is logged. We test agents against real examples before launch and monitor accuracy and cost afterwards.

How long does it take to build an AI agent?

A pilot for one workflow usually takes 3 to 5 weeks. Production agents with several integrations typically take 6 to 12 weeks. We share a fixed-scope proposal with milestones after a free consultation.

Do you build AI agents for small businesses?

Yes. Small teams often see the fastest return, because one agent can take over hours of repetitive admin each week. We usually start with a single workflow and expand once it pays for itself.

Ready to start with AI agents?

Tell us what you want to achieve. In a free 30-minute call, on Singapore or UK time, we will suggest the right approach, scope and timeline.