Capture live traffic, fine-tune and optimize, then deploy your own checkpoints to dedicated GPU endpoints. Choose hardware, set scaling limits, and select region. Stable latency, predictable cost, clear data residency.

Most AI decisions being made in enterprises right now will look outdated in 6 months. Not because leaders are getting it wrong. Because the ground keeps moving. New models. New architectures. New governance questions. Every single week. The leaders I see getting this right don't have all the answers. They stay close to the people actually building and shipping this stuff, and they learn fast. That's exactly why I'm tuning in to the Graphwise AI Summit 2026!!!!

2 days. 25 speakers. 20 sessions. October 7 and 8. Free and fully virtual. 700+ leaders have already signed up, from C-level executives to systems architects.

October 7: Business Track, Where ROI Meets Trust
For leaders deciding where to invest next:
Accenture on how Knowledge Graphs give Agentic AI the context it needs for real decisions
Roche on their Terminology and Interoperability System for building Minimal Viable Ontologies
Enterprise Knowledge plus industry panels on content catalogs, AI ROI, and energy-sector semantic solutions

October 8: Technical Track, Infrastructure and Implementation
For teams moving pilots into production:
Graphwise Platform Pulse, with the latest platform updates straight from their CTO
S&P Global and AstraZeneca on formal semantics for AI agents and unified governance
Cognizone, Avalara, and BitBang on production-grade agentive content chains and multi-industry Knowledge Graphs

If you're making these calls right now, this is 2 days well spent.

Can't make it live? You'll get the full recorded library afterward.

See you there.

BREAKING: Zendesk just launched Specialized Agents. I have been asking the same question in interviews for 2 years now. What can your AI agent actually do without a human finishing the job?

Across 750+ conversations with founders, CTOs and CDOs, and a lot of conference floors, the honest answer has almost always been the same. It answers. Then someone opens another tab and does the work.

That is what changed today.

What actually shipped -

1. Industry Agents. Prebuilt for specific business moments. First one is a Shopping Agent for ecommerce and retail, connected into Shopify, Stripe and Narvar. The full set of 10 commerce agents lands at AI Summit on November 10.

2. Custom Agents. Specialists you build for the work that’s unique to your business. Describe what they need to do in natural language using a no-code Agent Builder that wires agents to your own workflows, policies, data and APIs so they execute work rather than surface an answer.

Why this is not another chatbot release.

Trace one return request through an agent that can act:

intent.classify, returns.exchange context.load, profile and prior tickets shopify.orders.get, order state inventory.check, is the right size in stock policy.evaluate, is an exchange allowed narvar.label.create, write shopify.exchange.create, write outcome.commit, verified

4 reads. 3 writes. 0 humans.

The answer-only version of that same request is 1 read, 1 human and a refund that leaves the business.

The moment an agent holds write access to a system of record, your reporting changes. You stop counting tickets deflected and start counting orders saved.

The design choice I would pay attention to, 10 agents, not 1.

Returns, warranty, refunds, order tracking, fulfilment, billing, promotions, authentication, each scoped separately. That reads like a product decision. It is an operating model decision.

You cannot put a 500 dollar cap on "the AI". You can put one on stripe.refund:create. You cannot give "the AI" an owner. You can give one to the refunds agent.

One thing I will keep pushing on -

An agent that can act is an agent that can act wrongly.

3 questions I would put to Zendesk and to every vendor in this category:

Which systems does it write to on day one, with which credentials? What happens when confidence drops, and who owns that queue? How is a resolution defined? Zendesk verifies the outcome at 72 hours instead of closing a ticket at 24. That is the right instinct, and it is now the bar.

2026 was the year we agreed AI agents were real.
2027 is the year finance asks what they changed.

Full breakdown in this week's newsletter: the 6 layer architecture, the 10 agents as a routing table, and the 5 levels of agent autonomy. Link in comments.

Is specialization the right call, or does it just move the complexity into orchestration?

Genuinely curious what the builders here think.

In partnership with Zendesk.

The Ravit Show Data and AI, explained through the people building it. 1M+ community | 137K+ newsletter subscribers | 750+ interviews

Please reach out to Ravit@theravitshow.com for collaborations.

Best,
Ravit Jain
Founder & Host of The Ravit Show