# FluidStack vs Salesforce Agentforce (formerly Einstein)

FluidStack records 154,620 monthly visits with +7.3% month-over-month growth and Paid, Contact for Pricing pricing. Salesforce Agentforce (formerly Einstein) records 111,910,743 monthly visits with +2.2% growth and Freemium pricing.

| Metric | [FluidStack](https://openaitools.app/tool/fluidstack) | [Salesforce Agentforce (formerly Einstein)](https://openaitools.app/tool/salesforce-einstein) |
| :--- | :--- | :--- |
| Website URL | https://fluidstack.io | https://www.salesforce.com/agentforce/ |
| Categories | AI Developer Tools, AI Models, Large Language Models (LLMs) | AI App Builder, AI Developer Tools, AI CRM, No-Code&Low-Code |
| Pricing Model | Paid, Contact for Pricing | Freemium |
| Monthly Visits | 154,620 | 111,910,743 |
| MoM Growth Rate | +7.3% | +2.2% |
| Primary Market | United States | United States |
| Direct Visits | 47,869 | 60,741,009 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 1 | 20 |
| Supported Platforms | Website | Website |

## FluidStack

FluidStack is an AI compute provider that builds the physical layer underneath frontier model work: data centers, power, cooling and very large GPU clusters. Its public positioning is deliberately infrastructural rather than product-led — it describes building gigawatt-scale compute, bringing new sites online in months, and operating tens of millions of accelerators reliably. For teams training or serving large models, that translates into reserved, single-tenant-class capacity that is provisioned and operated for you rather than an instant, self-serve VM catalogue.

A distinguishing theme is the pairing of power and compute. FluidStack writes about redesigning compute and power infrastructure from first principles, developing off-grid solar to supply clusters, and using closed-loop cooling that fills tanks once and recirculates water indefinitely. It also emphasises building in the United States with onshored manufacturing, framing infrastructure ownership as a strategic question about which values shape the technology being built. For AI organisations, these are increasingly relevant because energy availability, not chip supply alone, is the binding constraint on scaling.

If you need a small number of GPUs for a day, FluidStack is probably not the fastest route; capacity is engaged at enterprise scale through a sales process. If you are planning a multi-month training run or a production inference fleet and want dedicated, purpose-built infrastructure with managed operations, it is a strong candidate to evaluate alongside the major hyperscalers and specialised GPU clouds.

**Pricing & Plans:** Enterprise and contact-for-pricing. FluidStack does not publish per-GPU-hour rates or a self-serve sign-up on its website; capacity is scoped and quoted through a direct sales conversation based on cluster size, duration and hardware. Catalogue listings classify it as a paid product requiring contact for pricing.

- **Datacenter-scale compute built in-house:** FluidStack designs and builds large AI data centers, including high-density campuses with significant per-site power capacity, rather than reselling capacity from other clouds.
- **GPU clusters for training and inference:** Clusters are architected for large-scale model training and inference, with high-bandwidth interconnect and orchestration suitable for distributed workloads.
- **Power and cooling engineered together:** The company develops off-grid solar and recirculating closed-loop cooling, treating power and water efficiency as core engineering problems.
- **Managed operations and reliability:** Smart hands, cluster provisioning and operations support let research teams focus on models while FluidStack runs the physical and orchestration layers.
- **US-built and onshored supply chain:** Data centers are built in the United States with onshored manufacturing of compute and power infrastructure, a deliberate supply-chain and sovereignty choice.

**Strengths:** Purpose-built AI infrastructure rather than generic cloud resale; Power, cooling and data center design handled in-house, which matters at scale; Managed provisioning and operations for large training and inference clusters; Explicit positioning on US-built, onshored infrastructure

**Limitations:** No published self-serve pricing or instant sign-up; access requires a sales conversation; Enterprise-scale focus means very small individual workloads may not be a fit; Capacity is concentrated in US locations, which may matter for latency-sensitive or data-residency-bound teams

[Profile (Markdown)](https://openaitools.app/tool/fluidstack.md)

## Salesforce Agentforce (formerly Einstein)

Originally launched as Salesforce Einstein for predictive CRM scoring and later Einstein Copilot for conversational assistance, Salesforce's flagship AI platform is now led by Agentforce. Built natively into the Salesforce Platform and grounded in unified enterprise data via Data 360 (formerly Data Cloud), Agentforce moves beyond rigid decision-tree chatbots and passive text generators to deploy autonomous AI agents capable of reasoning through multi-step problems and executing real business actions around the clock.

At the core of the platform is the Atlas Reasoning Engine, which evaluates incoming customer requests or system triggers, retrieves verified context from CRM records and external APIs, formulates an execution plan, and invokes Salesforce Flows, Apex classes, MuleSoft connectors, or verified Model Context Protocol (MCP) servers. In 2026, Salesforce expanded the platform with Long-Horizon Runtime—enabling agents to pursue multi-day workflows with human-in-the-loop oversight—alongside Multi-Agent Orchestration, Agentforce Voice for natural phone interactions beyond legacy IVR, and Agent Optimizer for real-time observability.

Organizations can launch pre-built role agents in clicks using the low-code Agent Builder or customize deterministic logic with Agent Script. Out-of-the-box roles include Customer Service Agents, autonomous Sales Development Representatives (SDRs) that qualify leads and book meetings, Sales Coaches for interactive deal role-play, Commerce Personal Shoppers, and Employee Coworker agents embedded directly inside Slack and Salesforce clouds.

**Pricing & Plans:** Existing Enterprise+ customers can start free via Salesforce Foundations ($0); usage-based options include Flex Credits at $500 per 100,000 credits ($0.10 per standard action, $0.15 per voice action), $2 per customer conversation, or $2 per Help Agent resolution, while unmetered employee seat add-ons cost $125–$150/user/month and Max (Agentforce 1) Editions start at $550/user/month.

- **Atlas Reasoning Engine & Long-Horizon Runtime:** Deconstructs complex queries into multi-step action plans grounded in Data 360, retaining state across days or weeks to complete multi-touch operational workflows with human escalation guardrails.
- **Low-Code Agent Builder & Agent Script:** Configure custom agents, subagents, natural-language instructions, and deterministic guardrails using existing Salesforce Flows, Prompt Builder templates, Apex code, and MuleSoft APIs.
- **Multi-Agent Orchestration & MCP Interoperability:** Coordinate specialized subagents across departments and connect securely to external enterprise tools through verified Model Context Protocol (MCP) servers from AgentExchange partners.
- **Agentforce Voice & Omnichannel Deployment:** Replace rigid telephone IVR trees with low-latency conversational voice agents alongside unified deployments across web chat, WhatsApp, SMS, mobile apps, and Slack.
- **Pre-Built Role Agents & Agent Optimizer:** Deploy ready-made Service, SDR, Sales Coach, Buyer, and Merchandiser agents out of the box, then monitor resolution accuracy and bottlenecks in near real time with Agent Optimizer.

**Strengths:** Deep native access to Salesforce CRM objects, Flows, Apex logic, MuleSoft integrations, and Data 360 without brittle third-party syncing.; Flexible 2026 billing models let enterprises choose between per-action Flex Credits ($0.10/action), $2 per conversation, $2 per resolution, or unmetered per-user licenses.; Enterprise-grade Einstein Trust Layer enforces zero data retention with external LLM providers, PII masking, and toxicity detection.; Supports open multi-agent interoperability via Model Context Protocol (MCP) and Long-Horizon multi-day task execution.

**Limitations:** Consumption pricing across Flex Credits, Data 360 credits, and seat add-ons is complex to forecast and prevents mixing Flex Credits and Conversation meters in the same org.; Requires clean, well-structured Salesforce CRM and Data 360 governance to avoid inaccurate agent actions.; Full enterprise capabilities carry a steep total cost of ownership, with top-tier Max / Agentforce 1 editions reaching $550 per user per month.

[Profile (Markdown)](https://openaitools.app/tool/salesforce-einstein.md)

## Frequently Asked Questions

### How do FluidStack and Salesforce Agentforce (formerly Einstein) compare in monthly traffic?

FluidStack has 154,620 monthly visits, while Salesforce Agentforce (formerly Einstein) has 111,910,743. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

FluidStack has a month-over-month growth rate of +7.3%; Salesforce Agentforce (formerly Einstein) has +2.2%.

### How does pricing compare?

FluidStack: Paid, Contact for Pricing. Enterprise and contact-for-pricing. FluidStack does not publish per-GPU-hour rates or a self-serve sign-up on its website; capacity is scoped and quoted through a direct sales conversation based on cluster size, duration and hardware. Catalogue listings classify it as a paid product requiring contact for pricing. Salesforce Agentforce (formerly Einstein): Freemium. Existing Enterprise+ customers can start free via Salesforce Foundations ($0); usage-based options include Flex Credits at $500 per 100,000 credits ($0.10 per standard action, $0.15 per voice action), $2 per customer conversation, or $2 per Help Agent resolution, while unmetered employee seat add-ons cost $125–$150/user/month and Max (Agentforce 1) Editions start at $550/user/month.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Automate work across thousands of apps — no code required | [.md](https://openaitools.app/tool/zapier-com.md) |
| 2 | [Intercom](https://openaitools.app/tool/intercom-com) | 4,471,110 | +2.7% | Free Trial, Paid | Exceptional customer support and helpdesk workflow automation, but less suited for broad enterprise CRM and sales execution. | [.md](https://openaitools.app/tool/intercom-com.md) |
| 3 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Delivers developer-first serverless endpoints optimized for generative media models rather than general-purpose infrastructure. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 4 | [RunPod](https://openaitools.app/tool/runpod) | 2,881,043 | +5.9% | Paid | Offers flexible on-demand GPU rentals and serverless endpoints, but lacks FluidStack's ultra-scale enterprise GPU clusters. | [.md](https://openaitools.app/tool/runpod.md) |
| 5 | [Gong – Revenue AI OS](https://openaitools.app/tool/gong-io) | 2,337,769 | +3% | Contact for Pricing | Superior revenue intelligence and call analytics, but specialized for sales insights rather than general agentic workflow automation. | [.md](https://openaitools.app/tool/gong-io.md) |
| 6 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | Visual no-code builder for custom AI agents, but lacks Salesforce's native enterprise data connectors and CRM structure. | [.md](https://openaitools.app/tool/mindstudio.md) |
| 7 | [Attio](https://openaitools.app/tool/attio) | 1,652,928 | -4.2% | Free Trial, Contact for Pricing | Modern customizable CRM with built-in AI agents, but lacks the massive enterprise ecosystem and scale of Salesforce. | [.md](https://openaitools.app/tool/attio.md) |
| 8 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Focuses on optimized serverless inference APIs and managed model hosting rather than raw cluster rentals. | [.md](https://openaitools.app/tool/together-ai.md) |
| 9 | [Vast.ai](https://openaitools.app/tool/vast-ai) | 1,257,554 | +2.8% | Paid | Delivers peer-to-peer GPU rental marketplaces for lower-cost experimentation, though with less enterprise infrastructure predictability. | [.md](https://openaitools.app/tool/vast-ai.md) |
| 10 | [Modal](https://openaitools.app/tool/modal-com) | 1,196,021 | +30.2% | Freemium, Contact for Pricing | Provides serverless Python container execution for cloud jobs, but lacks raw multi-node cluster provisioning controls. | [.md](https://openaitools.app/tool/modal-com.md) |

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Source: https://openaitools.app/compare/fluidstack-vs-salesforce-einstein

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