Customer and brand agents
Answer grounded questions, qualify demand, capture context, and route conversations without reducing the experience to a rigid script.
✓AI agent development
AI agent development company for production workflows.
We design the operating model around the agent, not just a chat interface. That means knowledge, tools, permissions, evaluations, escalation, and the channels where work already happens.
2,000+integration options via SketricGen
Web + channelsWhatsApp, Slack, and APIs
Humanapproval and handoff by design
What we deliver
Built around the use case, not the buzzword.
Sketric builds production AI agents, RAG systems, AI workforces, and multi-step automations with tools, evaluations, permissions, and human handoff.
Internal AI workforce
Give research, operations, support, and knowledge teams agents that can use defined tools and follow business guardrails.
✓MCP, API, and data integrations
Connect agents to CRM, ticketing, calendars, databases, messaging, internal services, and custom APIs with scoped permissions.
✓Evaluation and agent operations
Test retrieval, tool choice, task completion, refusal, safety, latency, cost, and escalation before expanding autonomy.
✓Where this creates leverage
A strong fit when the difficult part is the whole system.
We scope delivery around the operating reality, the people responsible for it, and the evidence needed to make the next decision.
A chatbot cannot complete the workflow
The system needs to retrieve context, use tools, update another system, or coordinate multiple steps before returning an outcome.
Knowledge changes too often for static answers
Ground the agent in governed sources with citations, freshness controls, access boundaries, and clear refusal behavior.
Autonomy must increase without losing control
We define what the agent can read, propose, change, or approve and where a person remains accountable.
Evidence in production
Proof from products and client systems.
Owned applications and selected client work show how AI decisions behave after launch.
Sketric-owned product
SketricGen
Our visual agent builder supports brand agents, AI workforces, tools, knowledge, channels, and multi-agent workflows.
↗ Related applied-AI workMuseum AI Guide
See a visitor-facing retrieval workflow built around governed content, metadata filters, and a conversational interface.
↗Questions teams ask
Useful answers before the first call.
Direct answers for teams deciding whether an AI system is worth building.
Are AI agents different from chatbots?+
A chatbot primarily responds. An agent can reason over a goal, retrieve context, choose tools, take multi-step actions, and escalate when it should not continue alone.
Can an AI agent take actions in our existing tools?+
Yes, where the required APIs or integrations are available. The workflow should define what the agent can see, what it can change, and when a person must approve the action.
How do you make AI agents reliable?+
We combine scoped tools, grounded knowledge, explicit handoff rules, traceable runs, representative test cases, and evaluation metrics tied to the business outcome.
How much does AI agent development cost?+
Cost depends on workflow breadth, integrations, knowledge preparation, permission design, evaluation depth, channels, and operating requirements. Discovery produces a scoped estimate instead of an unreliable one-size-fits-all number.
How long does it take to build an AI agent?+
A focused agent can be validated quickly, while a production workflow with several tools, permissions, channels, and evaluations requires more time. We sequence delivery around a narrow useful workflow first.
Have a project in mind?
Bring us the workflow, constraint, or ambitious idea.
We will help identify the narrowest useful starting point and the evidence needed to move forward.
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