Comparison

VDF AI vs Salesforce Agentforce

Two agent platforms with different centers of gravity. Agentforce is Salesforce-native — CRM, Data Cloud, Einstein Trust Layer, Flex Credits. VDF AI is portable orchestration across ecosystems with flat per-seat pricing and on-prem. Here's how they compare for enterprise buyers.

Pick VDF AI if

You need agents that span Salesforce and Microsoft, Google, Atlassian, GitHub, Slack, Zoom; or you need on-prem, EU residency, or predictable per-seat economics without Flex Credit translation.

Pick Agentforce if

Your workloads are Salesforce-centric — CRM, Service, Marketing, Field Service — and you want agents that inherit Salesforce identity, Trust Layer policies, and Digital Wallet metering by design.

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TL;DR

At a Glance

Four dimensions that drive most VDF AI vs Agentforce decisions.

Platform fit
VDF AI
Multi-ecosystem orchestration
Agentforce
Salesforce-native agents
Pricing
VDF AI
Flat per-seat
Agentforce
Flex Credits ($500/100k) + licenses
Deployment
VDF AI
Cloud, on-prem, EU residency
Agentforce
Salesforce cloud regions
Governance
VDF AI
Vault, RBAC, EU AI Act stack
Agentforce
Einstein Trust Layer + Salesforce admin
WHAT IS VDF AI?

A Multi-Cloud Enterprise AI Orchestration Platform

VDF AI is a multi-service platform for building, running, and governing AI agents at enterprise scale. It bundles a visual builder, a multi-provider runtime, Networks v3 orchestration, pre-built enterprise integrations across multiple ecosystems, and operational dashboards into one product you can deploy in your cloud, on-prem, or hybrid.

VDF AI is sold as a commercial platform with flat per-seat pricing and EU data residency options — designed for teams that cannot standardize on a single SaaS vendor for every integrated system.

Agent Hub6-step builder, multi-provider model routing, MCP tool registry, sandbox playground.
Networks v3Spec-driven DAG orchestration with intent decomposition and nested networks.
SEEMRSelf-Evolving Model Router — four live dimensions and LinUCB modes for governed enterprise AI. SEEMR architecture.
MCP ServerTool execution with connectors for Microsoft, Google, Atlassian, GitHub, Slack, Zoom, and API extension to Salesforce.
PortalAngular-based admin and operator UI for non-engineering stakeholders.
VaultEncrypted run records, artifacts, and full execution audit trail.
EU AI Act-alignedOn-prem, EU residency, conformity-oriented controls — built in.
WHAT IS AGENTFORCE?

Salesforce's Native Agent Platform

Agentforce is Salesforce's product line for autonomous and employee-facing AI agents embedded in CRM, Service Cloud, Field Service, Marketing, and related clouds. Builders use Agent Builder and Prompt Builder; grounding commonly flows through Salesforce records, Knowledge, and Data Cloud with policy enforcement through the Einstein Trust Layer.

Commercial packaging centers on consumption (Flex Credits, per-action rate cards, optional Conversation pricing for external agents), user licenses, and bundled Agentforce 1 editions. Digital Wallet provides usage analytics for Flex Credit and conversation products as described on Salesforce's pricing and product pages.

Agent Builder & Prompt BuilderAuthoring surfaces for topics, actions, and prompts inside Salesforce.
Data Cloud & CRM groundingUnify and activate customer data for retrieval and tool-backed agent steps.
Einstein Trust LayerData masking, auditing, policy, and zero-retention routing patterns for generative workloads.
Digital Wallet & Flex CreditsConsumption metering; public list price USD 500 per 100k Flex Credits at time of verification.
Service & Sales channelsNative reach into flows agents use alongside reps and automated service.
HyperforceSalesforce-managed regional infrastructure; not a bring-your-own-data-center Agentforce runtime.
SIDE BY SIDE

Feature by Feature

Salesforce claims verified against salesforce.com/agentforce/pricing; product capabilities against current Salesforce Help and Trust documentation.

CapabilityVDF AIAgentforce
Ecosystem reachMicrosoft 365, Google Workspace, Atlassian, GitHub, Slack, Zoom + API patterns for SalesforceSalesforce clouds (Sales, Service, Marketing, Data Cloud, Field Service, Industries)
CRM & service groundingVia integrations and APIs; not a duplicate of Salesforce's object modelNative CRM, Knowledge, and Data Cloud grounding
LLM routing & failoverOpenAI, Anthropic, Azure, Mistral, DeepSeek, Ollama, xAI + OpenAI-compatible endpoints with failoverModels and policies via Einstein Trust Layer and Salesforce-supported integrations (see current Salesforce model docs)
Orchestration modelNetworks v3 spec-driven DAG + Agent Hub; HTTP API for external callersAgent topics/actions inside Salesforce; Flow and platform automation as integration points
Multi-agent patternsNested networks, intent decomposition, cross-system coordination in one graphMulti-agent patterns within Salesforce product scope (verify current Agentforce multi-agent docs)
Usage & cost visibilityPer-node cost, latency, and energy metrics in product dashboardsDigital Wallet for Flex Credits and conversation usage (per Salesforce)
Employee vs customer agentsSame platform; authorization enforced via your IdP and VDF RBACDedicated packaging: Flex Credits, Conversation SKUs, unmetered add-ons (per rate card)
Channel deploymentHTTP API + first-class Teams, Slack, Zoom, etc.Salesforce UX, service consoles, and Salesforce-distributed experiences
Deployment optionsCloud, hybrid, on-premise with EU residencySalesforce-operated cloud; no customer-hosted Agentforce runtime
Pricing modelFlat per-seat platform feeConsumption (Flex Credits USD 500/100k list) + user licenses + optional Conversation pricing; editions to USD 550/user/mo list (verify SKUs)
Vendor boundaryPortable HTTP API; multi-vendor LLMDeeper coupling to Salesforce identity, objects, and billing SKUs
Governance storyEU AI Act-aligned controls, Vault audit, enterprise SSOEinstein Trust Layer + Salesforce compliance and admin tooling

Agentforce pricing figures verified May 2026 against salesforce.com/agentforce/pricing (USD list). Rates vary by currency and contract; Flex Credits and Conversation SKUs are mutually exclusive per org per Salesforce FAQs.

FAIR PLAY

Where Agentforce Wins

There are legitimate reasons Salesforce customers standardize on Agentforce.

Deepest CRM and Data Cloud context

Agents read the same objects, flows, and unified profiles your revenue and service teams already trust. No separate integration project to “teach” an external platform your Salesforce schema.

Einstein Trust Layer in-line

Policies, masking, and trust workflows are built for Salesforce's generative stack — a coherent story for teams that want AI governance inside the Salesforce certificate boundary.

Digital Wallet for consumption

Finance and platform owners can watch Flex Credits burn down with near-real-time attribution — important when variable consumption is an accepted operating model.

WHERE VDF AI WINS

What You Get on Day One

When your agent must coordinate beyond the Salesforce footprint — or live in your data center.

Cross-ecosystem orchestration

One Network can span Jira, GitHub, Slack, Zoom, Microsoft 365, Google, and Salesforce-connected backends without forcing every step through a single SaaS hub.

Predictable per-seat economics

No need to model Flex Credits per action, Conversation pools, and license stacks for every forecast cycle. Flat per-seat fits capex-friendly AI programs.

On-prem and air-gap paths

Regulated teams can keep inference and orchestration on hardware they operate. Agentforce does not offer an equivalent customer-run runtime.

LLM choice with failover

Bring OpenAI, Anthropic, Azure, open-weights via Ollama, and specialty providers with automatic failover — not only the models Salesforce bundles in a given edition.

EU AI Act-aligned platform controls

Built for conformity workflows, residency, and audit depth outside the Salesforce shared-responsibility narrative where you need your own evidence pack.

API-first portability

HTTP APIs and MCP tools keep orchestration swappable. You're not locked into Salesforce SKUs to add a new model or integration endpoint.

ARCHITECTURE

Two Different Operating Models

VDF AI is a platform you deploy. Agentforce is a Salesforce cloud service you subscribe to.

VDF AI

Customer-operated platform

  • Portal — Angular admin & operator UI
  • Agent Hub — agent lifecycle and routing
  • Networks v3 — spec-driven DAG orchestration
  • SEEMR — Self-Evolving Model Router (technical overview)
  • MCP Server — tool execution runtime
  • Vault — encrypted run records and artifacts
  • Postgres + Redis — persistence and queues

Runs in your VPC, your on-prem cluster, or VDF-managed cloud with residency options you choose.

Agentforce

Salesforce-managed service

  • Agent Builder / Prompt Builder — Salesforce authoring
  • Salesforce runtime — executes inside Salesforce cloud
  • Data Cloud & CRM — structured grounding sources
  • Einstein Trust Layer — policy and secure model access
  • Flex Credits + Digital Wallet — metering and analytics
  • Hyperforce regions — Salesforce data residency surface

Optimized when agents, humans, and records already live inside Salesforce. Extension outside relies on integration architecture.

DECISION GUIDE

Which One Should You Pick?

Map constraints first — ecosystem, deployment, and commercial model.

Choose VDF AI if…

  • Agents must coordinate across Salesforce, Microsoft, Google, Atlassian, GitHub, Slack, Zoom without standardizing on one vendor for everything.
  • You need on-prem, hybrid, or EU residency with your own audit evidence.
  • You want flat per-seat pricing instead of translating workloads into Flex Credits and rate cards.
  • You need multi-provider LLM routing with failover independent of a single SaaS roadmap.

Choose Agentforce if…

  • Your agents are anchored in Salesforce CRM, Service, Marketing, or Field Service data.
  • Einstein Trust Layer and Salesforce admin tooling are how you want AI governed.
  • Consumption-based Flex Credits or Conversation pricing matches your procurement model.
  • Standardizing on Hyperforce regions satisfies residency and you do not need a customer-run runtime.

Already invested in Agentforce?

You rarely have to rip and replace. Many teams keep Agentforce for Salesforce-native employee and customer journeys, and attach VDF AI for workloads that require multi-cloud orchestration, different LLM economics, or on-prem execution. We help map API boundaries, identity, and audit so both platforms coexist cleanly.

Discuss Coexistence
FAQ

Frequently Asked Questions

What buyers ask when evaluating VDF AI alongside Salesforce Agentforce.

Yes. VDF AI can orchestrate agents alongside Salesforce using standard patterns: HTTP APIs, event-driven hooks, and the same enterprise identity stacks many Salesforce shops already run. The difference vs Agentforce is architectural — VDF AI is not a Salesforce-native runtime. Agentforce agents are designed to live inside the Salesforce platform, Data Cloud, and Einstein Trust Layer. VDF AI is the better fit when your agents must coordinate equally across Salesforce and Microsoft 365, Google Workspace, Atlassian, GitHub, Slack, Zoom, or when you need full on-premise deployment.

Salesforce publishes Flex Credits at USD 500 per 100,000 credits (fungible across actions, prompts, translations, and voice actions), optional Conversation pricing at USD 2 per conversation (customer-facing agents; orgs use Flex or Conversation, not both per Salesforce FAQs), an Agentforce User License at USD 5 per user per month (requires Flex Credits), employee add-ons from USD 125 per user per month (unmetered employee Agentforce on listed clouds), and Agentforce 1 editions from USD 550 per user per month including bundled Flex Credits. VDF AI uses flat per-seat platform pricing — predictable for budgeting without translating agent actions into credit tables and rate cards. See Salesforce's public pricing page for current SKUs and regional currency.

Agentforce runs on Salesforce's cloud platform (Hyperforce regions). There is no customer-operated on-prem equivalent for the Agentforce runtime itself. VDF AI offers cloud, hybrid, and full on-prem deployments with EU AI Act-aligned controls and EU data residency.

Salesforce's Einstein Trust Layer is a first-party stack for secure, governed generative AI inside Salesforce — including zero-retention routing to external LLMs where configured, policy, and monitoring within the Salesforce trust boundary. VDF AI provides built-in audit trails, RBAC, Vault for run records, and EU AI Act-aligned controls as part of the platform you operate. If your compliance story is “everything must stay in Salesforce's certified boundary,” Agentforce aligns naturally. If you need portable orchestration across vendors and your own infrastructure, VDF AI aligns.

Agentforce leverages Salesforce's model strategy and Einstein Trust Layer integrations (models and availability change with Salesforce releases; verify the current model catalog in Salesforce Help). VDF AI supports OpenAI, Anthropic, Azure OpenAI, Mistral, DeepSeek, Ollama (local), xAI, and any OpenAI-compatible endpoint with built-in failover.

When your organization is already standardized on Salesforce, your agents must reason over CRM, Service, Field Service, or Marketing data in real time, you want Digital Wallet visibility into Flex Credit consumption, and Salesforce admin and compliance tooling is how you want to govern AI. For multi-ecosystem orchestration, on-prem, or flat per-seat economics, VDF AI is usually the stronger match.

See VDF AI complement or replace multi-cloud agent work.

Book a 30-minute architecture session and we'll map how VDF AI fits next to Agentforce — orchestration, integrations, LLM routing, and residency.

Explore VDF AI Agents