How much does Scale GenAI Platform cost?

Pricing is not public. It follows an enterprise sales motion with contracts only. You must contact sales for specific pricing details, as there is no self-serve sign-up option available for this platform.

Which AI models does the platform support?

The platform is model-agnostic. It supports multiple providers including OpenAI, Google, Meta, and Mistral. This flexibility allows enterprises to choose the best model for their specific agent tasks without being locked into a single vendor.

Can I deploy this within my own cloud infrastructure?

Yes. SGP deploys inside the customer's own AWS, Azure, or GCP VPC. This ensures data stays in place and meets the security requirements of regulated enterprises that cannot ship data to third-party SaaS environments.

What data sources can the platform connect to?

It includes data connectors for sources like Confluence, SharePoint, and S3. These connectors allow the platform to reason over internal data while keeping it in place, supporting RAG workflows over enterprise-specific information.

Is there a free or open-source version available?

Scale open-sources parts of the stack, such as Agentex and AgentOps. Teams can use these components to prototype before signing a contract. However, the full platform requires an enterprise contract and deep integration work.

Scale GenAI Platform

Enterprise agent platform from Scale AI that connects your data, orchestrates multi-agent workflows, and learns from human feedback inside your own VPC.

Enterprise· Contact sales; enterprise contracts onlyFine-tuningMulti-model (OpenAI, Google, Meta, Mistral)7.1 / 10

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In short

Scale GenAI Platform is an enterprise agent system that runs inside your VPC. It connects internal data, orchestrates multi-agent workflows, and learns from human feedback.

Best for

Pick Scale GenAI Platform if you're a regulated enterprise that needs production agents running on internal data inside your own cloud, with auditability and an RLHF-style feedback loop.

Skip if

Skip it if you're a startup or indie developer who just wants to ship an agent this week without a procurement process.

Scale GenAI Platform (SGP) is Scale AI's full-stack enterprise offering for building, deploying, and continuously improving AI agents that reason over a company's internal data. It bundles four layers in one product: data connectors (Confluence, SharePoint, S3 and friends) that leave data in place, an agent runtime that handles long-running async workflows and multi-agent coordination, a monitoring and evaluation layer with source-cited outputs and audit trails, and a feedback loop that turns human corrections into training signals.

The pitch is squarely aimed at regulated enterprises that can't ship data to a third-party SaaS. SGP is model-agnostic (OpenAI, Google, Meta, Mistral and others) and deploys inside the customer's own AWS, Azure, or GCP VPC, which is the main reason a Fortune 500 would pick it over building on raw LangChain or LlamaIndex. Pricing isn't public; this is an enterprise sales motion with onboarding from Scale's services arm. The note that this category is 'fine-tuning' is roughly right because the learn-and-improve loop is the differentiator, but it's really an end-to-end agent platform.

Scale also open-sources pieces of the stack (Agentex, AgentOps), so teams can prototype on the OSS components before signing a contract. Expect deep integration work rather than a self-serve sign-up.

Editor's take

This is the grown-up answer to 'how do we do agents at a bank?' rather than the fun answer to 'how do I prototype one over the weekend?'. Scale's edge is the labeling and feedback pipeline behind it, which most agent frameworks lack. Worth a call if you're already in an enterprise pilot; otherwise look elsewhere.

— The AI Tool Bible editorial team

Pros

✅ Deploys inside your own VPC on AWS, Azure, or GCP so data never leaves
✅ Model-agnostic, avoiding lock-in to a single LLM vendor
✅ Built-in evaluation, monitoring, and human-feedback loop for continuous improvement
✅ Backed by Scale's mature data-labeling and RLHF operation
✅ Open-source components (Agentex, AgentOps) let you prototype before buying

Cons

⚠️ No public pricing; enterprise sales cycle only
⚠️ Overkill and too expensive for small teams or solo builders
⚠️ Heavy implementation effort versus plug-and-play agent SaaS

Use cases

enterprise-agentsrag-over-internal-datamulti-agent-workflowshuman-feedback-loopsregulated-industries

Frequently asked

How much does Scale GenAI Platform cost?: Pricing is not public. It follows an enterprise sales motion with contracts only. You must contact sales for specific pricing details, as there is no self-serve sign-up option available for this platform.
Which AI models does the platform support?: The platform is model-agnostic. It supports multiple providers including OpenAI, Google, Meta, and Mistral. This flexibility allows enterprises to choose the best model for their specific agent tasks without being locked into a single vendor.
Can I deploy this within my own cloud infrastructure?: Yes. SGP deploys inside the customer's own AWS, Azure, or GCP VPC. This ensures data stays in place and meets the security requirements of regulated enterprises that cannot ship data to third-party SaaS environments.
What data sources can the platform connect to?: It includes data connectors for sources like Confluence, SharePoint, and S3. These connectors allow the platform to reason over internal data while keeping it in place, supporting RAG workflows over enterprise-specific information.
Is there a free or open-source version available?: Scale open-sources parts of the stack, such as Agentex and AgentOps. Teams can use these components to prototype before signing a contract. However, the full platform requires an enterprise contract and deep integration work.