Voiceflow named a 2026 Best Software Award winner by G2
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For years, "Salesforce AI" meant Einstein. If you evaluated a Salesforce chatbot before 2024, you were looking at Einstein Bots and a set of Einstein-branded predictions bolted onto the CRM.
That's not the story anymore. Salesforce has reorganized almost its entire product line around a new brand, Agentforce, and the old Einstein names are being retired or absorbed. If you're evaluating Salesforce for AI customer service in 2026, the guide you read two years ago is describing a product that barely exists now.
This is what Salesforce AI actually is today: what Agentforce does, how it differs from the Einstein Bots you may remember, what it costs, and where a CRM-agnostic platform makes more sense.
Salesforce AI now comes in two layers, and the newer one is where all the momentum is.
The older layer is Einstein, the brand Salesforce has used since 2016 for its machine-learning and generative features. The customer-facing piece was Einstein Bots, a rule-based chatbot you built inside Service Cloud to greet customers, answer common questions, and route conversations to a human. It works, but it's a decision-tree bot: it handles one query at a time, follows the paths you scripted, and can't reason or act on its own.
The newer layer is Agentforce, launched in late 2024 and now Salesforce's flagship AI product. Agentforce is a platform for building autonomous AI agents that use large language models to interpret a request, reason about it, and take action across your Salesforce data, not just reply from a script. The customer-service version is the Agentforce Service Agent, the direct successor to Einstein Bots.
The practical takeaway: if someone says "the Salesforce AI chatbot" in 2026, they usually mean Agentforce. Einstein Bots still exists and is still supported, but Salesforce's new investment is going almost entirely into Agentforce. If you're starting fresh, that's the product to evaluate.
The gap between the two is the same gap that separates a scripted chatbot from a real AI agent.
If you already run Einstein Bots, Salesforce's own guidance is to plan your roadmap around Agentforce. The rule-based bot is the past; the reasoning agent is where the product is going.
Here's the part that trips up anyone reading older documentation. At Dreamforce 2025, Salesforce renamed much of its stack around the Agentforce brand:
None of this changes what the products do, but it does mean the terminology in most "Salesforce Einstein" guides is now a version or two behind. When you're comparing notes with a vendor or a consultant, make sure you're both talking about the current names.
This is the question the older guides skip, and it's the one that matters most for a buying decision. Salesforce has changed Agentforce pricing more than once, and in 2026 there are three overlapping models you'll run into:
The honest framing: Agentforce cost is consumption-based and stacks on top of the Salesforce licenses you already pay for. The "AI" line item is separate from your seats, and it grows with usage. Before you commit, model the real workload, not the demo. This is the same ROI math any serious enterprise AI rollout needs.
It depends almost entirely on how committed you already are to Salesforce.
That trade, ecosystem depth versus flexibility and cost, is the decision. It's worth weighing against a dedicated agent platform before you commit.
If you want an AI agent that isn't tied to one CRM's roadmap, model, or pricing meter, Voiceflow is the platform most teams compare against Agentforce. The honest distinction: Agentforce is an AI layer inside the Salesforce ecosystem, while Voiceflow is a dedicated platform for building and deploying agents into whatever stack you already run.
Where Voiceflow pulls ahead for serious agent builds:
You don't have to choose one or the other. A common setup is to build the agent in Voiceflow and sync conversations and contacts back to Salesforce by API, so you keep the CRM you rely on and run an agent that isn't capped by it.
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Salesforce's AI has two brands. Einstein is the older machine-learning and generative layer, including the rule-based Einstein Bots. Agentforce, launched in late 2024, is the newer agentic-AI platform and is now Salesforce's flagship. Most 2026 conversations about "the Salesforce AI chatbot" are about Agentforce.
Agentforce is Salesforce's platform for building autonomous AI agents. Unlike the rule-based Einstein Bots, an Agentforce agent uses large language models to reason about a request, act across your Salesforce data, and handle multi-step tasks end to end. The customer-service version is the Agentforce Service Agent.
Agentforce pricing is consumption-based and comes in a few forms: roughly $2 per conversation, Flex Credits (about $500 per 100,000 credits, where a standard action is around $0.10), or per-user add-ons that can run from about $125 to $550 per user per month. It stacks on top of your existing Salesforce licenses, so budget for usage, not a flat fee.
Yes. Einstein Bots is still supported for existing rule-based deployments, but Salesforce's new investment is focused on Agentforce. If you're building from scratch in 2026, Salesforce's own guidance is to start with the Agentforce Service Agent rather than Einstein Bots.
For teams that want a CRM-agnostic, model-agnostic agent with native voice and production controls, Voiceflow is the most common alternative to Agentforce. It integrates back into Salesforce (or any CRM) by API, so you can keep your CRM and still run an agent you fully control.
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