Current facts
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Agents or Agentforce?
Decide
Agentforce is a real agentic platform, and when you already run on Salesforce with clean data it is hard to beat on its home turf. The catch is that its home turf is Salesforce — the data, the licenses, the admin time, and the governance model all live inside the platform. Custom AI is the other road: agents built for your actual stack and delivered done-for-you, wherever your revenue data happens to sit.
Quick verdict
Choose Agentforce when you are already a Salesforce shop, your customer data is clean and unified in Data Cloud, and you have the admin or implementation team to configure agents and keep them governed. Its prebuilt Service and Sales agents drop straight onto your CRM records. Choose a custom AI agent system when the work reaches past Salesforce into your product database, billing, warehouse, or outside APIs, when you want it built and run for you without standing up a Salesforce project, or when per-action consumption pricing gets unpredictable at your volume. Both are real. The deciding question is whether the job lives inside the Salesforce wall or crosses it.
Side by side
AI Agents vs Agentforce at a glance
The dimensions that matter when the stack has to support qualified leads, fast follow-up, clearer pipeline, or better conversion.
| Dimension | AI Agents | Agentforce |
|---|---|---|
| What it is | Custom agentic AI built for one workflow, on the model and tools that fit the job, and delivered done-for-you. | Salesforce's agentic layer. Prebuilt and custom agents, built in Agent Builder, run on the Atlas reasoning engine and ground on your Salesforce data. |
| Who builds and runs it | We do. We plan it, build it, wire the integrations, and hand you something that runs. No new platform for your team to staff. | Your Salesforce admins or an implementation team configure agents in Agent Builder, then own the tuning, testing, and upkeep. |
| Data and CRM reach | Any system with an API — Salesforce, HubSpot, your product database, billing, warehouse, internal tools, outside data. | Strongest inside Salesforce, grounded on clean Data Cloud profiles. Reaching outside needs connectors or MCP actions you set up. |
| Hosting and data control | You choose — your cloud, your model provider, VPC or on-prem if compliance needs it. Data stays where you put it. | Runs on Salesforce infrastructure behind the Einstein Trust Layer (masking, zero data retention). Data lives in the platform. |
| Governance and evals | Evals, guardrails, and plan trails you own and can change. We build the review harness around your risk tolerance. | Inherits Salesforce permissions, sharing rules, and the Trust Layer. Strong native controls, governed inside Salesforce's model. |
| Pricing shape | A planned build plus ongoing model inference and upkeep. Cost tracks the work, not a per-action meter. | Editions plus consumption (Flex Credits) billed per agent action, so cost tracks usage and can climb at volume; verify on salesforce.com. |
| Time to value | Weeks. Discovery, build, evals, launch, planned to the workflow that moves revenue first. | Fast on native use cases when data is clean; longer if you first have to unify Data Cloud, fix data quality, and set governance. |
| Best fit | Teams not all-in on Salesforce, work that spans many systems, or anyone who wants the build handled for them. | Salesforce-native orgs with clean Data Cloud data and the admin capacity to configure and govern agents. |
Vendor pricing and feature claims change frequently. Verify details directly with each platform before committing.
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What changes often
Features and limits move
AI features, usage caps, add-ons, integration limits, and support tiers can change faster than a comparison page can stay current.
Workflow decision
Map your own work
The right answer depends on the repeat workflow, source data, owner, review step, integration needs, and measurable business result.
Choose AI Agents
When this path fits
- You are not all-in on Salesforce, or you run a different CRM entirely.
- The work spans systems outside Salesforce — product database, billing, warehouse, support tools, outside APIs.
- You want it delivered done-for-you, without standing up a Salesforce project or hiring admins to run it.
- You need evals, guardrails, and a governance model you control, not one bounded by a single platform.
- Per-action consumption costs would get unpredictable at your volume, and you want spend that tracks the build.
Choose Agentforce
When this path fits
- You are already a Salesforce shop — Sales Cloud, Service Cloud, and your reps live in it daily.
- Your customer data is clean and unified in Data Cloud, so agents have trustworthy records to ground on.
- The prebuilt Service and Sales agents cover your use case and you want to start from a template.
- You have admin or implementation-team capacity to configure agents and keep them tuned.
- You value native Salesforce permissions, sharing rules, and the Einstein Trust Layer over building governance yourself.
How we would actually decide
The platform is only useful if the system moves revenue
Here is the honest cut: Agentforce is the right call for Salesforce-native orgs, and custom AI is the right call when the work crosses the Salesforce wall or you don't want to staff the build. That one line settles most of these decisions before we open a laptop.
If your revenue actually runs on Salesforce — reps in Sales Cloud, cases in Service Cloud, a Data Cloud profile that is clean and current — then Agentforce is grounded in exactly the data it needs, and the prebuilt agents give you a running start. Fighting that with an outside build is swimming upstream, and we would tell you to use Agentforce and mean it.
The picture flips when the job does not sit neatly inside Salesforce. The lead's real behavior is in your product database, the money truth is in billing, the fulfillment status is in a warehouse system, and half the context lives in tools Salesforce never sees. Now you are paying to bridge every one of those into the platform, per action, while governing an agent that only sees part of the story. That is where a custom agent built directly against your systems, and handed to you done-for-you, wins on reach, on cost you can predict, and on control.
We do not have a horse in the Salesforce race, so we will tell you straight which side of the wall your problem is on. That read is exactly what our AI System Plan produces: one page showing where agents move revenue for you, and whether Agentforce or a custom build is the cheaper way to get there.
Frequently asked
AI Agents vs Agentforce questions answered
Is Agentforce better than a custom AI agent?
Neither is better in the abstract. Agentforce is the stronger choice when you run on Salesforce with clean Data Cloud data and have an admin to configure and govern it. A custom AI agent is stronger when the work reaches outside Salesforce, when you want it delivered done-for-you, or when consumption pricing gets unpredictable at your volume. The deciding question is which side of the Salesforce wall your problem lives on.
Do I need Salesforce to use Agentforce?
In practice, yes. Agentforce is Salesforce's agentic layer, and it grounds on your Salesforce data, working best when that data is unified in Data Cloud. It can reach some outside tools through connectors and MCP actions, but it is built to run inside the Salesforce platform. If you are not on Salesforce, a custom agent is usually a more direct path than adopting the whole platform just to get one agent live.
How much does Agentforce cost?
Salesforce prices Agentforce with a mix of editions and consumption, where agent actions draw down Flex Credits, so your cost tracks how much the agents actually do. That is easy at low volume and can climb as usage grows, which is why teams put usage controls on it early. We do not quote their numbers here because they change, so verify on salesforce.com.
Can Agentforce work with systems outside Salesforce?
Yes, to a point. Agentforce can call external tools through connectors and, as of 2026, MCP actions you register, so it is not sealed off. But every outside system you bridge is more setup, and the agent still reasons from a Salesforce-centered view. When most of the context lives outside Salesforce — product data, billing, warehouse, internal tools — a custom agent built directly against those systems is usually simpler and cheaper to run.
What does done-for-you actually mean compared to Agentforce?
With Agentforce, you or an implementation team configure the agents in Agent Builder and then own the tuning, testing, and upkeep. Done-for-you means we do that work: we plan it, build it, wire the integrations, set the evals, and hand you an agent that runs. You get the outcome without staffing a Salesforce build or adding a platform your team has to learn and maintain.
How do we decide between Agentforce and a custom build?
Draw the line at the Salesforce wall. If the work lives inside Salesforce and your Data Cloud data is clean, Agentforce is grounded where it needs to be and the prebuilt agents give you a head start. If the work crosses that wall into other systems, or you would rather not run the platform yourself, a custom build wins on reach, predictable cost, and control. Our AI System Plan makes that call on your actual stack, on one page.
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Next step
Turn the comparison into a revenue decision
If the wrong stack is slowing response speed, qualification, handoff, or reporting, the AI System Plan tells us whether a build should exist.