# Labelbox vs Salesforce Agentforce (formerly Einstein)

Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. Salesforce Agentforce (formerly Einstein) records 111,910,743 monthly visits with +2.2% growth and Freemium pricing.

| Metric | [Labelbox](https://openaitools.app/tool/labelbox) | [Salesforce Agentforce (formerly Einstein)](https://openaitools.app/tool/salesforce-einstein) |
| :--- | :--- | :--- |
| Website URL | https://labelbox.com | https://www.salesforce.com/agentforce/ |
| Categories | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools | AI App Builder, AI Developer Tools, AI CRM, No-Code&Low-Code |
| Pricing Model | Contact for Pricing | Freemium |
| Monthly Visits | 762,803 | 111,910,743 |
| MoM Growth Rate | -22.8% | +2.2% |
| Primary Market | United States | United States |
| Direct Visits | 370,024 | 60,741,009 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 0 | 20 |
| Supported Platforms | Website | Website |

## Labelbox

Labelbox occupies an unusual position in the AI stack: it does not primarily sell a chatbot or a generator, it builds the environments and data that models learn from plus the agents that take over recurring engineering and research work. The homepage claim is direct — frontier AI labs train on Labelbox environments and expert data, while engineering and research teams hand their recurring backlog to agents running on Recursion. A recent Series E of more than $100 million signals a heavily funded bet on that thesis.,For enterprises, the newer half of the product is Recursion. Agents are triggered by real signals — a failing build, a PagerDuty alert, a new dependency release, a fresh model checkpoint, or a Monday morning schedule — and then work in the background until the job is done. The examples the company promotes are concrete deliverables rather than summaries: a tested pull request with a preview link, a postmortem draft in Confluence with every event sourced, an ablation table naming the changes that mattered, or a patch for each exposed service after a critical CVE. A grader agent scores each run, and the graded session leaves behind memories, notes and skills that the next session reads before it acts.,The original foundation remains the data business: labeling, annotation, curation and model evaluation supported by expert human reviewers, used for computer vision, NLP, supervised fine-tuning, RLHF and red teaming. In practice the two halves reinforce each other, since the environments that produce high-quality training data are the same environments where agents learn to do real work. Pricing is enterprise-style, routed through sales conversations and shaped by data volume and agent usage, with no public self-serve tier.

**Pricing & Plans:** Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases.

- **Data labeling and expert annotation:** Structured annotation, curation, model evaluation and human-in-the-loop review across vision, language and generative tasks, used to build the training and eval data behind production models.
- **Autonomous agent sessions:** Recursion agents start on their own from builds, alerts, commits, checkpoints and schedules, then work in the background until the task is finished and reviewable.
- **Domain specialists by function:** Specialist agents cover software engineering, reliability, security, ML research, evals, R&D, product and finance workflows, from flaky test fixes to postmortem drafts and vulnerability patches.
- **Graded outcomes that compound:** Every agent run is scored by a grader, and graded sessions leave memories, notes and skills that the next session reads before acting, so quality compounds over time.
- **Native tool and data integrations:** Agents operate against the tools teams already use, including GitHub, Jira, Linear, Slack, Datadog, PagerDuty, BigQuery, Databricks, Vercel and cloud providers.

**Strengths:** Covers both sides of the problem: training and eval data production plus agents that act on recurring work; Backed by a recent $100M+ Series E and adoption by frontier AI labs, indicating real funding and demand; Agent runs produce concrete deliverables with proof — tests, reruns, ablations — rather than unverified suggestions; Integrates with the toolchain teams already run: GitHub, Jira, Linear, Slack, Datadog, PagerDuty, BigQuery and Databricks

**Limitations:** No self-serve pricing or open signup: everything routes through a sales conversation, which slows down evaluation; The platform assumes real engineering and research infrastructure (GitHub, cloud providers, data warehouses) to deliver value; Positioning has shifted quickly toward autonomous agent sessions, so teams wanting only labeling workflows may find it heavier than needed

[Profile (Markdown)](https://openaitools.app/tool/labelbox.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 Labelbox and Salesforce Agentforce (formerly Einstein) compare in monthly traffic?

Labelbox has 762,803 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?

Labelbox has a month-over-month growth rate of -22.8%; Salesforce Agentforce (formerly Einstein) has +2.2%.

### How does pricing compare?

Labelbox: Contact for Pricing. Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases. 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 | [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) |
| 4 | [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) |
| 5 | [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) |
| 6 | [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | +6.6% | Freemium, Contact for Pricing | Streamlines end-to-end computer vision workflows from annotation to model deployment, but lacks Labelbox's general enterprise agent orchestration. | [.md](https://openaitools.app/tool/roboflow.md) |
| 7 | [Appen](https://openaitools.app/tool/appen-com) | 665,840 | +0.2% | Contact for Pricing | Relies heavily on managed human-in-the-loop workforce services for data validation, offering less self-serve technical tooling than Labelbox. | [.md](https://openaitools.app/tool/appen-com.md) |
| 8 | [Scale](https://openaitools.app/tool/scale) | 616,915 | +12.5% | Contact for Pricing | Delivers enterprise-grade labeling and model evaluation at massive scale, but often requires higher enterprise budgets than Labelbox. | [.md](https://openaitools.app/tool/scale.md) |
| 9 | [Chatbase](https://openaitools.app/tool/chatbase) | 396,383 | -7% | Freemium, Paid | Simple no-code AI chatbot deployment, but less equipped for complex enterprise-grade CRM automation and multi-system agents. | [.md](https://openaitools.app/tool/chatbase.md) |
| 10 | [SuperAnnotate](https://openaitools.app/tool/super-annotate) | 386,034 | +37.4% | Free Trial, Contact for Pricing | Offers robust multimodal annotation and workflow automation, featuring slightly more intuitive data curation pipelines for computer vision teams. | [.md](https://openaitools.app/tool/super-annotate.md) |

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

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