Your data
Connect to data sources like Confluence, SharePoint, S3, and more. SGP structures that data through optimized bespoke pipelines, not a generic one.
Reliable infrastructure is at the core of what we do.
Scale GenerativeAI Platform gives teams the tools to build, deploy, and continuously improve agents that reason over your data, run reliably at scale, and get smarter every time they're used.
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Connect Data
Connect to enterprise data from your sources, wherever they live. Our engine ingests, labels, and structures it, getting it AI-ready with your data staying right where it is.
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Build + Execute
Deploy, host, and orchestrate agents that reason over your data. Implementation supports long-running async workflows, multi-agent coordination, and any model (again with no vendor lock-in).
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Evaluate + Monitor
Automated and human feedback is received to manage, debug, and improve agent performance through semantic layer monitoring, evaluation scoring, and full trace transparency, so you get visibility in real time.
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Learn + Improve
Human feedback is ingested back into the model engine as a learning signal. Operations telemetry becomes training data, making the agent self-improving over time, so your systems keep pace with the frontier without rebuilding from scratch.
Run your entire agent lifecycle in one place.
Most teams stitch together various tools and call it a stack. SGP gives you a unified foundation – from data pipelines to live agent monitoring – built to work cohesively from day one.
You own the stack. Scale works inside it.
SGP works agnostically across your current tools, frameworks and models. No migrating.
No switch in providers.
Your Cloud
Deploy securely within your own VPC. Full support for AWS, Azure, and GCP with enterprise-grade governance at every layer.
Your models
Test, fine-tune, and deploy across all major models — OpenAI, Google, Meta, Mistral, and more. Switch without rebuilding. Optimize without starting over.
Agents are easy to build and hard to trust. (That’s where we come in.)
All Your Data. AI-Ready.
Every agent is built and tested against your specific enterprise standards — your workflows, your rules, your definition of good — before it ever touches production.
Agent execution + operation
Scale manages the full complexity of running agents at enterprise scale — long running, async, and multi-agent workflows — so your team can focus on outcomes, not operations.
Reliable and trustworthy deployment
Every agent that goes into production comes with a full audit trail, source-cited outputs, and enterprise-specific oversight built in so you always know what your AI did and why.
The more you use it the smarter it gets.
SGP captures behavioral data from institutional knowledge, encodes expert judgement, continuously improves agent performance over time. The result: agents that make better outputs, without requiring manual retraining cycles.
PERFORMANCE OVER TIMETHE FLYWHEEL PROCESS
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Usage becomes data
Every query, decision, and outcome is captured and structured automatically. Nothing is wasted.
Human in the loop
Capture human feedback and transform raw usage signals into structured, high-quality data.
Data fuels improvement
Real usage data is converted into targeted improvements; no manual work, no waiting.
Improvement compounds
Higher-quality agents get used more. More usage generates better data. The cycle continues.
Your Dialect emerges from the feedback loop. Shaping AI to think like your best employees.
At its core, Scale AI Dialect is a decision map that sets you apart from the competition. It doesn’t just track how data flows, but how decisions are made. As your decision layer improves, the ‘why’ is learned and encoded by expert judgements, eventually becoming as autonomous as your guardrails allow it.
SGP Platform Differentiators
Capabilities
Scale AI SGP
Open Source
In House Builds
Model Builder
Long-running async agents
SGP’s Agentic Infrastructure layer (Agentex and AgentOps) natively enables long-running agents designed for complex tasks.
Open source frameworks lack the managed infrastructure and enterprise support needed for reliable, long-running async agents at production scale.
Success depends on your team’s internal bandwidth and expertise to build and maintain this infrastructure.
Continuous learning flywheel
With SGP, your models and systems improve over time through ongoing human feedback and co-developed IP you own.
Open source tooling can support feedback loops, but requires significant internal investment to build pipelines that continuously improve model quality.
Building a reliable learning flywheel is complex and resource-intensive. We’ve found this is the kind of nested complexity that stalls in-house efforts.
Possible, but requires significant custom infrastructure. Most teams struggle to sustain it over time.
Built-in evaluation & benchmarking
Eval-driven development is core to reliable AI. We draw on our expertise in deploying for governments and on access to SEAL, our in-house frontier benchmarking lab.
Enterprise compliance & governance
Scale's partnership model includes compliance, data governance, and IP ownership structures suited for regulated industries.
Open source tools have no built-in compliance framework. You're responsible for all security, governance, and regulatory requirements.
Human-in-the-loop oversight
Reliable AI is built around human + AI collaboration, which is baked into SGP.
Security that holds up to government standards
View safety standards +DoD IL4 Provisional AuthorizationSOC 2 Type IIISO 27001FedRAMP High Authorized
Trusted by industry leaders
Frequently Asked Questions
- Talk to an expert
Scale's flexible, interoperable, and largely open-source technology toolkit ensures no platform lock-in, with your enterprise retaining full ownership of their data and agent code.
