Executing support actions in connected systems for end-to-end support resolution

Last week, Pylon launched its new agentic support platform.
It reinforced something we've been thinking about a lot.

Individual AI agents are already surprisingly capable.
They can write emails.
Update tickets.
Create tasks.
Summarize meetings.

Those are becoming solved problems. The hard part is keeping ten agents, five humans, and six enterprise systems synchronized while the underlying state changes every minute.

Every enterprise workflow eventually becomes a distributed systems problem.
That's where enterprise AI gets interesting. The challenge shifts from reasoning to coordination.
Shared memory.
Deterministic execution.
Human checkpoints.
Recoverability.
Auditability.

The first wave of AI products automated tasks. The next wave coordinates work.
I'm extremely bullish on autonomous agents. But the real unlock happens when humans and agents work in tandem ;)

Salesforce just put a price tag on AI agents: $0 until one actually resolves a case.

Rolling out in the Summer '26 release (GA July 2026), the new Agentforce Help Agent only charges per resolution — not per conversation, not per seat. That's a quiet but huge shift: vendors are now betting their revenue on whether the agent actually works.

What it means for you:

→ The risk of "AI theatre" drops — you pay for outcomes, not demos.
→ But it raises the bar on *your* setup: outcome-based pricing only pays off if your agent can reach real systems and resolve, not deflect.
→ The bottleneck moves from "should we try agents?" to "is our service data + workflow ready for them to act?"

Our take: outcome-based pricing is the best thing to happen to enterprise AI buyers in a while — it aligns the vendor with you. Just don't let "deploys in minutes" fool you into skipping the integration work that makes resolutions possible.

Are you ready to pay per resolution — or would your current setup leave the agent stuck at step one?

#Aptclouds #Agentforce #Salesforce #CustomerService #EnterpriseAI

With the General Availability of Service Agent and MCP tools in Microsoft 365 Copilot, service organizations continue to get the benefits of Copilot in customer service, now powered by the rich business context and grounded intelligence of both Dynamics 365 and Microsoft 365. Whether they’re new in career or experienced customer service representatives, your employees get tools from Microsoft to help deliver a better support experience for your customers. With this release, we have added rich, interactive app-in-chat experiences, ensuring that customer service representatives do not need to solely rely on text-based conversational UX. Employees can investigate issues, navigate complex processes, and complete tasks without leaving the conversation. The result is a more connected, action-oriented experience that helps service professionals move from understanding to resolution faster in Dynamics 365 Customer Service and across Microsoft 365 apps.

Fin can be used as a Service Agent on top of HubSpot and Freshworks, meaning you can use the world’s best Agent without migrating off your helpdesk.

Hubspot and Freshdesk customers can now:
- Get Fin live, integrated, and working seamlessly in less than an hour
- Delivering a 76% average resolution rate
- Across all customer channels (voice, email, chat, social, and more)
- Resolving complex queries that require reading and writing to third party systems
- With everything fully configurable to follow the unique policies of every individual business.

Hey Z-Admin, Zendesk Relate is over, and if you missed it, here’s a quick summary of the most relevant announcement 👇

The main topic was something Zendesk is calling the Autonomous Service Workforce. What does that mean? In simple terms, Zendesk is moving from traditional bots that only deflect tickets to AI agents that can work across channels, understand context, and take action.

✅ Agent Builder: A no-code interface to create, test, and optimize your own AI agents, adapted to your policies, workflows, data, and business logic.

✅ Omnichannel AI Agents: AI agents will be able to operate across messaging, email, voice, ChatGPT, Gemini, and other environments while keeping context across channels.

✅ Copilots for different roles: Not only for agents. Zendesk is also expanding Admin Copilot, Knowledge Copilot, and Analyst Copilot to help detect issues, improve workflows, find knowledge gaps, and analyze trends.

✅ Action Flows + MCP + connectors: Zendesk wants AI to do more than answer questions. The goal is for AI agents to execute actions across your external systems.

✅ Resolution-based pricing: Zendesk is moving toward a model where customers pay for verified resolutions, not just usage or volume.

What do you think?