

INTRODUCING
Chatbot SX for Agentforce
Inaccurate or off-brand AI responses can become escalations, compliance breaches, or social blowups in minutes. Chatbot SX brings proactive controls, oversight, and precision knowledge to every AI-led interaction without changing your existing Agentforce workflows.
“SupportLogic helps our customers become more knowledgeable and find the right answers faster, resulting in improved customer satisfaction and operational efficiency.”
Vineet Puri, SVP and Co-Head, Global Client Services, Cvent
cases Evaluated Per month
Languages Supported
+
countries Supported
Deepen Your ROI with Salesforce Agentforce
Chatbot SX is a layer of real-time signal intelligence, governance, and contextual knowledge on top of your chatbot for instant oversight and smarter AI-led conversations.




Flag anomaly patterns, sentiment drift, and off-policy outputs immediately.
Merge chat transcripts, voice transcripts, and case data in a unified view.
Equip Agentforce with verified answers from your knowledge base and enterprise systems so bots ground responses in facts—not guesses.
Enforce style, tone, compliance, and product claims.
Prevent Inaccurate and Off-Brand AI Responses
Prevent escalations, viral backlash, compliance breaches, and lost customers. Here’s what’s at stake:
Reduce Hallucinations by Complementing Agentforce’s Einstein Trust Layer
Chatbot SX brings dynamic grounding, data masking, toxicity/accuracy scanning, and zero-data-retention agreements with third-party LLMs—so answers stay tethered to approved data. We work hand-in-glove with the Atlas Reasoning Engine—Agentforce’s brain that plans, acts, and validates iteratively—so your governance layer sees the plan and the proof, not just the final text.
Precision RAG consistently prepares the data from any source for the process of precise question-answering, to make use of a wide variety of retrieval methods for finding the most relevant knowledge, analyzing only the information required to produce an answer. Guardrails automatically evaluate whether a query is relevant to the knowledge domain and if the sources can provide an accurate answer. This helps minimize errors related to topic mismatches or missing data, ensuring more reliable and accurate responses.

Precision RAG Outperforms LLMs in Accuracy
In complex support, the main sources of knowledge will not be an organized knowledge base but instead past cases. This type of data cannot simply be thrown at a LLM if you’re expecting consistency. This fact can be seen in the benchmark data below, comparing us to an OpenAI embedding in retrieval of internet-available vs. domain-specific data scenarios (March 2024).
Data type | Collection | Success@5 ADA-2.0 | Success@5 SupportLogic | Failure@5 ADA-2.0 | Failure@5 SupportLogic | No. of Queries | No. of Documents |
---|---|---|---|---|---|---|---|
Public | Ember | 91% | 96% | 9% | 4% | 102 | 123 |
Slightly technical | Owllabs | 91% | 94% | 9% | 6% | 250 | 694 |
Technical | 8X8 | 75% | 86% | 25% | 14% | 250 | 3,227 |
Domain specific | Waters | 78% | 87% | 22% | 13% | 400 | 13,504 |
Frequently Asked Questions
No. It works alongside Agentforce, enhancing accuracy, oversight, and resolution rates without replacing your existing system.
Higher Resolution Rates – solve more complex queries without handoffs.
Oversight & Governance – prevent hallucinations, bias, and off-brand answers.
Reduced Escalations – fewer unnecessary transfers to live agents.
We connect via Agentforce objects/APIs MessagingSession + ConversationEntry (and related conversation services) to capture every message in real time, with zero disruption to your customer-facing workflows.
A four-step process handles every chat conversation:
Capture
Chatbot SX consumes every ConversationEntry within each MessagingSession, including bot and end-user turns.
Enrich
We join transcripts with case history, account health, and prior interactions for full context.
Evaluate
Signals detect sentiment shifts, anomaly patterns, and off-brand content; Trust-Layer-aligned checks ensure sensitive data isn’t exposed and responses remain grounded.
Correct or Escalate
Inject Precision RAG answers, adjust tone, or route to a human when confidence is low or policy requires supervision.
Chatbot SX is not intended to serve as the chat experience or the UI layer. Our offering primarily enables ingestion of Agentforce interactions into SupportLogic, providing comprehensive observability across all customer touchpoints and allowing SupportLogic AI agents to be invoked directly from within Agentforce via API calls.
The chat interface and conversation orchestration are fully managed by Agentforce on both the agent and customer-facing sides. Agentforce supports embeddable web and mobile chat widgets as well as native interfaces of messaging platforms such as WhatsApp, SMS, Messenger, Slack, and others. It also facilitates event-driven handoffs from virtual agents to live agents, based on configurable triggers defined within the Agentforce platform.
SupportLogic is SOC 2 Type II, ISO 27001, GDPR/CCPA/HIPAA compliant, and aligns to Salesforce’s Trust Layer patterns like masking and zero-retention with third-party LLMs. SupportLogic also complies with the EU AI Act.
Customers typically see escalation rates drop by half, CSAT scores climb 20%+, and FCR improve significantly within weeks.
Currently, Chatbot SX is built for Agentforce. However, SupportLogic does support other chat tools (Zendesk, Freshdesk, and so on) as case objects linked to a support case.
Get ahead of the next AI support crisis.
Built to integrate with any enterprise chatbot or autonomous agent. Agentforce is first, and your AI oversight layer scales as your roadmap expands.