# Modal vs Salesforce Agentforce (formerly Einstein)

Modal records 1,196,021 monthly visits with +30.2% month-over-month growth and Freemium, Contact for Pricing pricing. Salesforce Agentforce (formerly Einstein) records 111,910,743 monthly visits with +2.2% growth and Freemium pricing.

| Metric | [Modal](https://openaitools.app/tool/modal-com) | [Salesforce Agentforce (formerly Einstein)](https://openaitools.app/tool/salesforce-einstein) |
| :--- | :--- | :--- |
| Website URL | https://modal.com | https://www.salesforce.com/agentforce/ |
| Categories | AI Developer Tools, AI API, Large Language Models (LLMs), AI Models | AI App Builder, AI Developer Tools, AI CRM, No-Code&Low-Code |
| Pricing Model | Freemium, Contact for Pricing | Freemium |
| Monthly Visits | 1,196,021 | 111,910,743 |
| MoM Growth Rate | +30.2% | +2.2% |
| Primary Market | United States | United States |
| Direct Visits | 845,636 | 60,741,009 |
| Review Score | 4.8 | 4.4 |
| Saved Count | 3 | 20 |
| Supported Platforms | Website | Website |

## Modal

Modal provides cloud infrastructure aimed squarely at AI and data teams. The core idea is that developers write ordinary Python, decorate functions or define container images, and Modal takes care of the underlying compute: scheduling containers, attaching GPUs, autoscaling from zero and back, and exposing endpoints over HTTPS. Infrastructure concerns like networking, storage, and capacity management are abstracted away, so a workload that runs on a laptop can run the same way across a fleet.

The platform is organised around a few primitives. Functions handle serverless compute and can fan out across thousands of GPUs for parallel or batch work. Sandboxes provide isolated environments for coding agents, reinforcement learning rollouts, and other untrusted code, with sub-second start times and support for very high concurrency. Training covers fine-tuning, reinforcement learning, and evaluation on single or multi-node GPU capacity. On the inference side, Modal offers OpenAI-compatible endpoints for open-weight models and lets teams deploy custom stacks and tune endpoints to match their traffic shape.

Underneath, Modal runs its own container runtime and image system designed for large images and fast GPU scheduling, along with a distributed filesystem for fast access to model weights and datasets. Capacity is drawn from a multi-cloud pool spanning many regions, with automatic routing to available hardware and continuous fleet health checks. Billing is usage-based, charged by the second while code runs, with granular cost controls. The company offers a free starting allowance and scalable paid usage, and markets to enterprises with SOC 2 Type II compliance and HIPAA readiness.

**Pricing & Plans:** Modal uses usage-based pricing billed by the second: a free monthly compute allowance gets you started, then you pay for the CPU, memory, and GPU resources your workloads consume. Enterprise plans and startup credits are available, and custom pricing can be discussed with sales.

- **Serverless Python functions:** Write plain Python, attach GPUs or containers, and deploy HTTPS endpoints that autoscale with traffic and scale to zero when idle.
- **Sandboxes for agents:** Launch isolated, secure environments for coding agents, RL rollouts, and untrusted code, with sub-second starts and support for over a million concurrent sandboxes.
- **Training and fine-tuning on demand:** Run fine-tunes, LoRA, full training, and reinforcement learning on elastic single or multi-node GPU capacity with no quota requests.
- **Model inference and endpoints:** Serve LLMs and image, video, or audio models through OpenAI-compatible endpoints, or bring your own inference stack and let Modal handle the infrastructure.
- **Fast storage and multi-cloud capacity:** A distributed filesystem loads large images and model weights at full bandwidth, while a pool spanning 20+ clouds routes workloads to the right hardware and region.

**Strengths:** Python-native developer experience with almost no infrastructure boilerplate; Scales from zero to thousands of GPUs with per-second, usage-based billing; Sandboxes are well suited to agentic and untrusted-code workloads; Multi-cloud capacity spans many regions with out-of-the-box observability and enterprise compliance

**Limitations:** Billed by real usage, so heavy GPU workloads can get expensive quickly without cost controls; Some advanced inference and enterprise features require working with the team rather than self-serve signup; The serverless model can feel less familiar to teams used to managing their own VMs or Kubernetes clusters

[Profile (Markdown)](https://openaitools.app/tool/modal-com.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 Modal and Salesforce Agentforce (formerly Einstein) compare in monthly traffic?

Modal has 1,196,021 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?

Modal has a month-over-month growth rate of +30.2%; Salesforce Agentforce (formerly Einstein) has +2.2%.

### How does pricing compare?

Modal: Freemium, Contact for Pricing. Modal uses usage-based pricing billed by the second: a free monthly compute allowance gets you started, then you pay for the CPU, memory, and GPU resources your workloads consume. Enterprise plans and startup credits are available, and custom pricing can be discussed with sales. 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 | Extremely fast serverless execution optimized specifically for generative media models rather than general Python code. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 4 | [RunPod](https://openaitools.app/tool/runpod) | 2,881,043 | +5.9% | Paid | Provides flexible GPU infrastructure and serverless endpoints, though less focused on pure Python function decorators. | [.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 heavily on managed open-source model inference APIs rather than arbitrary custom container execution. | [.md](https://openaitools.app/tool/together-ai.md) |
| 9 | [Vast.ai](https://openaitools.app/tool/vast-ai) | 1,257,554 | +2.8% | Paid | Rent cloud GPUs by the second from a global marketplace | [.md](https://openaitools.app/tool/vast-ai.md) |
| 10 | [Nebius](https://openaitools.app/tool/nebius) | 1,145,711 | +10.7% | Paid, Contact for Pricing | Delivers robust enterprise GPU clusters and managed inference, requiring more infrastructure setup than Modal's serverless approach. | [.md](https://openaitools.app/tool/nebius.md) |

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

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