Agentic AI systems that plan, decide, and act — not single-shot prompts.

Autonomous AI agents that break a goal into steps, call your tools and APIs, and carry a task to completion — built on Claude and other leading LLMs, wired into the systems your team already runs on, with the guardrails to trust what they do.

Agentic AIClaudeTool CallingLLM OrchestrationRAG
Who it's for

Built for teams whose workflow needs judgment, not just data-moving

Off-the-shelf automation tools hitting a wall

Zapier and Make handle the simple cases, but your workflow needs actual judgment — reading context, deciding what to do next, and adapting when the situation doesn't match the template.

A multi-step process no single prompt can cover

The task spans several systems and decisions — look something up, decide what it means, take an action, verify the result — which is exactly what breaks a plain chatbot or single-call LLM integration.

AI you can't yet trust to act on its own

You like what agents could do, but without clear guardrails and visibility into what the agent decided and why, handing it real actions feels too risky to ship.

What's included

Everything you need to ship

Multi-step planning & tool use

Agents that break a goal into steps, call your APIs and internal tools, and adapt the plan as new information comes in.

Guardrails & human-in-the-loop

Scoped permissions, approval steps for high-stakes actions, and full visibility into what the agent did and why — so autonomy doesn't mean losing control.

Built on Claude and leading LLMs

Model choice driven by the task — reasoning depth, latency, and cost — not locked to a single vendor.

Wired into what you already use

Integrated into your existing stack — CRM, support inbox, internal dashboard — not a separate tool your team has to remember to open.

Reviews

5.0★ on Google, in their words

Left on our Google Business and Clutch profiles, quoted exactly as written.

SigmaticAI delivered exceptional results in building our custom Agentic AI system. Ketan Khamgaonkar’s technical mastery in autonomous agent design, system integration, and workflow execution made project delivery seamless. Implementation was prompt, and the AI agents immediately streamlined our operations. Highly recommend Ketan and the SigmaticAI team!
Madhuvanti Bapat12 reviews · Google
They delivered on time and were very proactive in recommending new capabilities for the marketplace.

SigmaticAI delivered a complete MVP with five feature areas, including a vetted caregiver marketplace, membership plans, courses, and events. The team was proactive, talented, and knowledgeable, recommending new capabilities and using the latest technology.

Ara VazquezFounder, The Raising Club · Clutch
Working with SigmaticAI has been an outstanding experience. A special mention to Ketan Khamgaonkar, whose deep technical expertise, clear communication, and structured approach made a significant difference throughout our project. Delivery was prompt, and the AI solutions implemented have had an immediate, positive impact on our workflow. Highly recommend Ketan and the SigmaticAI team!
Dr. Chaitanya V. Bhore10 reviews · Google
I have purchased clinic software from them.. it has improved efficiency and treatment quality for my patients.. Also it’s very useful for accurate accounting..
Abhishek SambreDoctor · 14 reviews · Google
Good experience with development and automating process. Great management and quick handover.
Kusumika sinha roy30 reviews · Google

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FAQ

Common questions

What's the difference between a chatbot and an agentic AI system?

A chatbot answers questions. An agentic system plans a sequence of steps, calls tools or APIs to gather information or take action, and adapts based on what it finds — closer to a junior team member executing a task than a search box.

How much does agentic AI development cost?

For one agentic workflow scoped end-to-end and connected to your existing systems, expect roughly $15K–$60K depending on how many tools it needs to call and how much judgment it has to exercise. We'll scope your specific case on a call rather than guess from a range.

How do you keep an autonomous agent from doing something wrong?

Scoped tool permissions, an approval step before any high-stakes or irreversible action, and logging that shows exactly what the agent decided and why — the same guardrails you'd want from a new hire before you'd trust them unsupervised.

Have a project like this in mind?

Tell us what you're building — we'll tell you the fastest honest path to live.

Other ways we can help