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Union.ai vs Lamini

Union.aiLamini

Bottom line: Union.ai for mL engineers; Lamini for regulated and data-sensitive enterprises.

Union.aiUnion.ai

Durable AI and ML orchestration built on Flyte 2

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Lamini

Enterprise platform to build and tune LLMs on your own data

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Votes00
PricingFreemiumPaid
CategoryMlopsMlops
Tags
mlopsorchestrationflyteworkflowsdurable-runtime
llm-fine-tuningenterprise-aimemory-tuningon-premisesai-infrastructure
Best for
  • ML engineers
  • Data platform teams
  • Production ML orgs
  • Regulated and data-sensitive enterprises
  • Teams needing on-prem LLM deployment
  • Organizations prioritizing factual accuracy
Pros
  • Built on proven open-source Flyte
  • Flyte 2 durable, infrastructure-aware runtime
  • Author workflows in pure Python, no new DSL
  • Automatic recovery from failures
  • Enterprise features: observability, SSO, RBAC
  • Strong focus on data control and secure deployment
  • On-premises and VPC options for compliance
  • Memory tuning aimed at reducing hallucinations
  • Runs on both AMD and NVIDIA accelerators
  • Backed by respected investors and founders
Cons
  • Python-centric workflow authoring
  • Orchestration concepts have a learning curve
  • Enterprise features are paid
  • Kubernetes knowledge helps for self-hosting
  • Overkill for very simple pipelines
  • Enterprise-focused with limited self-serve transparency
  • No permanent free plan
  • Published usage rates are indicative and often sales-led
  • Requires ML expertise to operate effectively
  • Smaller company than some infrastructure incumbents

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