Lamini
Generative AI software
Large language model operationalization (LLMOps) software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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$480 per month
Free Trial unavailable
Free version
Small
Medium
Large
- Banking and insurance
- Healthcare and life sciences
- Professional services (engineering, legal, consulting, etc.)
What is Lamini
Lamini is an LLMOps platform focused on building and operating domain-specific large language model applications using enterprise data. It supports workflows such as data preparation, fine-tuning/training, evaluation, and deployment for teams that need more control than prompt-only approaches. The product is typically used by engineering and data science teams to create internal copilots, knowledge assistants, and task automation systems with governance and performance requirements.
End-to-end LLM lifecycle
The platform centers on operational workflows needed to move from data to a deployed model-backed application. It addresses common steps such as training/fine-tuning, evaluation, and serving rather than only providing a chat interface. This aligns with organizations that need repeatable processes for iteration and release management.
Enterprise data adaptation focus
Lamini is positioned around adapting models to proprietary datasets and domain language. This is useful for internal assistants where accuracy depends on company-specific terminology and documents. It provides a path beyond generic generative AI features found in broader productivity tools.
Engineering-oriented integration
The product is designed for technical users who integrate LLM capabilities into existing applications and pipelines. This typically includes API-driven usage and support for programmatic evaluation and deployment patterns. It can fit teams that want to standardize how LLM components are built and maintained across projects.
Requires technical implementation effort
LLMOps platforms generally assume engineering and ML/DS involvement for data preparation, evaluation design, and deployment. Organizations looking for out-of-the-box end-user features may find the setup heavier than general-purpose generative AI tools. Time-to-value depends on data readiness and internal MLOps maturity.
Less suited for non-technical teams
Compared with products aimed at sales, marketing, or content creation, Lamini is not primarily a workflow app for business users. Teams may still need separate front-end experiences (e.g., chat UI, CRM integration) built on top of the platform. This can increase total implementation scope.
Public details may be limited
Some buyers may find fewer publicly documented benchmarks, third-party validations, or standardized pricing information than with larger, suite-based vendors. This can make procurement and technical due diligence more time-consuming. Enterprises may need deeper vendor-led evaluation to confirm fit for security, compliance, and scale requirements.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Free | $0 / month | Open-source software and open datasets; LaminDB (open-source); LaminHub: collaborate on existing databases. |
| Team | From $480 / month | Hosted data platform + support; everything in Free; LaminHub (manage your own databases); Benchling, Seqera/Nextflow, and custom integrations; Pre-release integration tests for pipelines; Private Slack channel. The pricing UI shows a "-25%" label and a payment-frequency toggle (Annually/Monthly). |
| Enterprise | Custom | On-prem platform + support; everything in Team; On-prem deployment; SSO; Contact sales for custom pricing. |
Seller details
Lamini, Inc.
Unsure
Private
https://lamini.ai/
https://x.com/lamini_ai
https://www.linkedin.com/company/lamini-ai/
