- Highly regulated environments with strict AI audit requirements
- If you need detailed, publicly documented AI-specific compliance mappings, formal third-party assessments, and mature enterprise controls for every Gradient feature, hyperscalers (or specialized enterprise AI platforms) may be a safer choice.
- Mission-critical production AI where billing caps are unacceptable
- If your business cannot tolerate usage being capped pending invoice payment (as described in pricing docs), you may prefer direct-to-provider APIs or enterprise contracts with clearer SLAs and billing arrangements.
- Teams needing maximum platform maturity today
- If you have low tolerance for “public preview” features (ADK, Router, Evaluations) and the risk of breaking changes, consider more established stacks or narrow solutions (e.g., direct OpenAI/Anthropic APIs + your own RAG pipeline).
- Deep hyperscaler-native environments
- If your org is already standardized on AWS/GCP/Azure IAM, networking, logging, and procurement, the incremental value of adding DigitalOcean may not justify the operational overhead.
- Current limitations acknowledged by the vendor
- The platform includes multiple “public preview” features (ADK, Router, Evaluations per docs), implying potential changes and weaker SLA expectations.
- Limitations reported by users
- Reported max_tokens cap behavior in the Playground and long-running/stuck indexing jobs (from a G2 review excerpt).
- Data privacy documentation constraints
- DigitalOcean’s Gradient AI Data Privacy page states: “We do not store agent inputs or outputs on DigitalOcean infrastructure for any models.”
- Practical limitation / ambiguity
- This statement does not necessarily describe what third-party model providers store when you use commercial models, nor does it fully specify logging/retention behavior for conversation logs referenced in other posts (buyers should reconcile these statements carefully and ask for authoritative clarification).
- API / integration constraints
- The platform spans:
- API endpoints (DigitalOcean API `api.digitalocean.com` for managing agents/workspaces)
- inference base URL (`inference.do-ai.run` for serverless inference)
- Teams must manage two conceptual planes (control plane vs inference plane), which can complicate network controls, secrets management, and observability.