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  1. Home
  2. Compare
  3. Agentforce vs custom
  1. Home
  2. Compare
  3. Agentforce vs custom

Agentforce vs custom agents

You do not need a turf war. You need three answers. Agentforce when the work and the permissions live in Salesforce. A custom stack (ADK, CrewAI, OpenAI Agents, MCP) when they do not. Hybrid when you have both — that is most mid-market orgs we see.

Ask us which seat you are inAgentforce page

The three questions

If a partner quotes a fixed Agentforce price before these, walk. Context first. Platform second.

Question 1

Where do the users already work?

Agentforce

Salesforce console, Experience Cloud, Slack-if-Salesforce-is-the-source.

Custom stack

Slack-first field teams, WhatsApp, a portal that is not Experience Cloud, or no CRM login at all.

Question 2

Where does the system of record live?

Agentforce

The org. Knowledge, cases, opportunities, Data Cloud grounding that already respects sharing.

Custom stack

ERP, warehouse, product DB, or documents Salesforce would only see as a middleman.

Question 3

Who must own the control plane?

Agentforce

You want Salesforce procurement, Trust Layer, and inherited profiles. Security is tired.

Custom stack

You need BYOM, MCP connectors, A2A between runtimes, or an audit trail Salesforce will not emit.

Cost is the wrong first question

Agentforce consumption and a custom platform TCO usually land closer than the sales decks imply. You are choosing who owns identity, audit, and the connector layer — not which logo is cheaper in month one.

  • We will not quote a build before a data-readiness pass.
  • We will not start with more than three agents in v1.
  • Einstein Copilot is not Agentforce. If someone says it is, they have not shipped this.
  • MCP is how an agent calls tools. It is not a permission system. See the MCP guide.

MCP vs point-to-point

The 2025 failure mode was a custom connector per tool. MCP standardizes that. It does not give you auth, least privilege, or an audit trail. Those sit on top. Point-to-point still makes sense for one system and one agent. The moment a second runtime appears, point-to-point is debt.

MCP

Standard tool and data connectors. Inventory them. Scope them. Log them. Then A2A if agents must call other agents.

One-off APIs

Fine for a single Agentforce action into one system. Fragile the day CrewAI or ADK needs the same object.

MCP in production · MCP implementation

How we would pick a runtime for a use case

  • Customer service — Retell on voice, Claude or OpenAI for reasoning, Cognee for memory, Agentforce or Agent Fabric when the case lives in Salesforce.
  • Sales pipeline — Agentforce if the rep lives in the org. OpenAI or Claude plus n8n and CrewAI when enrichment and follow-up leave Salesforce.
  • IT helpdesk — Gemini or OpenAI plus ADK and MCP. Agentforce only if the ticket already is a Salesforce case.

See the full stack

Agentforce vs custom FAQ

Why do Agentforce pilots stall?

Usually context, not the model: messy Knowledge, no Data Cloud or equivalent grounding, sharing rules the agent cannot inherit, and no plan for transcript review after go-live. See data readiness and the pilot-to-production guide.

Is custom always more expensive?

Not on a three-year TCO. Custom means you own hosting, evals, and connectors. Agentforce means you own consumption and Salesforce’s constraints. We price the control plane, not the logo.

Can we run both?

Yes. That is the usual answer. Agentforce for CRM-native work. Custom agents plus MCP and A2A for everything that is not. Agent Fabric when Salesforce agents need a control plane.

Bring the process. We will name the runtime.

Or we will tell you this is not an agent problem yet.

Get a frank assessment