FAQ Deep Dives
What makes Upstage AI different from other LLM providers?
Upstage doesn’t just train bigger models — it trains *smarter* ones. Every Solar and Syn model is rigorously evaluated on domain-specific benchmarks, grounded in verified sources, and stress-tested for consistency across long-context, multi-step reasoning tasks. Paired with document intelligence built from the ground up — not bolted on — Upstage delivers end-to-end automation that’s both powerful and production-safe.
How does Upstage AI handle sensitive or regulated documents?
By design: zero data retention, optional on-prem deployment, automatic PII detection and masking, and strict role-based access controls. All document processing pipelines are GDPR- and HIPAA-aligned, with audit trails and configurable redaction policies — ensuring compliance isn’t an afterthought, but a foundation.
Can I fine-tune Solar models on my proprietary data?
Absolutely. With Upstage Fine-tuning Studio, domain experts can curate datasets, label outputs, and launch custom-trained models — all within a governed, version-controlled environment. No ML PhD required.
Is Upstage AI compatible with existing document management or CRM systems?
Yes. Prebuilt connectors for Salesforce, ServiceNow, DocuSign, SharePoint, and common ECM platforms are available. Custom integrations are supported via REST APIs, webhooks, and SDKs for Python, Node.js, and Java.
Do you offer SLAs, audit logs, or SOC 2-compliant deployments?
All enterprise plans include guaranteed uptime SLAs (99.9%), granular usage and security audit logs, and SOC 2 Type II certification. On-prem and air-gapped deployments meet additional standards including ISO 27001 and FedRAMP readiness.
What’s new in Solar Pro 2 compared to earlier versions?
Solar Pro 2 introduces enhanced multistep reasoning, improved financial and legal domain fluency, expanded multilingual support (12+ languages), and tighter integration with Upstage’s document intelligence stack — enabling true “document-to-decision” workflows.
How does Document Parse improve over traditional OCR engines?
Unlike legacy OCR, Document Parse combines layout-aware vision models with semantic understanding — preserving tables, headers, footers, and cross-references while correcting scan artifacts, skew, and font inconsistencies. It outputs structured JSON with confidence scores, making downstream extraction reliable and auditable.