# Sobot Upgrades its AI Agents, Moving from Answers to Results

- Link: https://www.thailand-business-news.com/pr-news/sobot-upgrades-its-ai-agents-moving-from-answers-to-results
- Published: 2026-08-13T10:00:00+07:00
- Author: PR Newswire

**_Built to Solve, Backed by a Full System of Support_**

SINGAPORE, Aug. 13, 2026 /PRNewswire/ — Sobot, the agentic customer contact platform,
announced an upgrade to its AI Agents. This upgrade didn’t come from a smarter model
alone, but from a fundamental change in how Agents think and act.

 [⌊The Agentic Customer Contact Platform⌉](https://mmx.prnasia.com/media/MS1969054/20260812222842EDT_image_1.jpg?id=OA2876695&p=medium600)

The Agentic Customer Contact Platform

**What’s New in Sobot Agents**

**Reasoning in Action: From Answering Questions to Getting Things Done**

Previously, Sobot followed a workflow-trigger pattern: businesses built a workflow
in advance, mapping out how the Agent should respond to each customer behavior. 
Once a customer’s intent was recognized, the Agent simply followed that path. It
couldn’t adapt when a situation fell outside the workflow, and nothing fed back 
into the Agent’s own decision-making until the process had run its course.

The upgraded Sobot Agents work differently, running on a continuous loop of reasoning,
acting, and observing, a pattern known as ReAct. Take a return request: instead 
of following a workflow, the Agent works out what information it still needs, checks
it against what the customer has already shared, and asks for the rest. Workflows
still suit scenarios that need a fixed process; this is simply a more adaptive option.
RAG keeps every answer grounded in the right knowledge, and ReAct turns that understanding
into a finished task.

The foundation of Sobot Agents lies in a unified resource layer of knowledge, skills,
tools, MCPs, memory, and variables, centrally managed and shared across every Agent
rather than configured separately. A skill built to handle one type of request only
needs to be created once, then any Agent can call on it automatically whenever it
recognizes a matching scenario, without rebuilding it from scratch.

**Conversational Building: From Expert Configuration to Simplified Setup**

Building an AI Agent used to mean specialist-level setup: bot styles, prompts, knowledge
bases, and even more, each on its own separate page. In the updated Sobot Agents
Studio, businesses simply describe what they want to build in a conversation, the
same way they might explain a task to a colleague, covering the relevant business
materials and what the Agent is expected to do. The Studio then pulls up the right
settings on its own, and no page switching is needed. Knowledge, skills, and tools
all come together in one place.

**Ask AI for Data: Performance Insights in Natural Language**

The upgrade introduces "Ask AI for Data", changing how businesses assess their own
AI Agents’ performance. Sobot used to bring performance data together in one dashboard,
but businesses could only view preset templates. With so many metrics available,
managers had to dig through them, find the ones that mattered, and work out the 
comparisons on their own. Now, instead of reading a dashboard, managers can simply
ask a question in natural language and get a direct answer, complete with trend 
interpretation, anomaly flags, and next steps to take.

**Nexus and Experts: The Infrastructure and Expertise Behind Every Agent**

Sobot Agents handle customer interactions independently, but they don’t run in isolation.
That independence is backed by two more layers: Nexus and Experts.

Sobot Nexus is the unified infrastructure every Agent runs on. It connects every
channel customers might come from, including website and app chat, voice, email,
and social media such as WhatsApp, Facebook Messenger, and Instagram, into a single
platform. It also gives agents a unified workspace: when a request needs a human
touch, it transfers there with the full conversation history, so nothing needs to
be repeated. An AI Copilot works alongside the human agent throughout, helping them
handle the conversation more efficiently.

Sobot Experts stay involved throughout a business’s journey with Sobot Agents. AI
Strategists design implementation plans aligned with businesses’ goals; Deployment
Specialists configure and launch Agents for stable operation; AI Trainers refine
models using real conversation data; and Operation Analysts monitor performance 
and flag where to adjust next. Rather than stepping back once a system is delivered,
Experts keep observing and tuning, driving steady gains in accuracy.

**Sobot: Redefining What AI Solves in Customer Contact**

"We’re moving AI in customer contact from a supporting role to a leading one. The
question is no longer how well AI can assist a human agent, but how much AI can 
resolve on its own. That’s the direction we see the whole industry heading, and 
it’s the direction we’re building Sobot toward," said Yi Xu, CEO of Sobot.

This upgrade reflects that shift: Sobot Agents are now built to finish a customer’s
request, not just respond to it, freeing up businesses’ people for what genuinely
needs a human touch.

For more information, please visit [https://www.sobot.io/](https://www.sobot.io/).

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