
Lamini は月間 4,158 訪問、前月比成長率 +0.3%、料金体系フリーミアム、料金は要問い合わせを記録しています。Scale は月間 616,915 訪問、成長率 +12.5%、料金体系料金は要問い合わせを記録しています。

Lamini is an enterprise LLM platform for building, fine-tuning, controlling and deploying custom large language models. It targets teams that need their own accurate, private models rather than a generic API: you bring your data, fine-tune open models on the platform, and serve them with tuned runtimes designed to reduce hallucinations. It covers use cases like text-to-SQL, classification, RAG and function calling, and is known for running workloads on AMD GPUs.
Scale is an enterprise AI company that supplies the data, evaluation and deployment layers behind production AI. Its Data Engine sources and labels training data for frontier models, its evaluation work benchmarks model capability, and its platform teams help enterprises and governments move AI systems from pilot into real operations.

Lamini is an enterprise LLM platform for building, fine-tuning, controlling and deploying custom large language models. It targets teams that need their own accurate, private models rather than a generic API: you bring your data, fine-tune open models on the platform, and serve them with tuned runtimes designed to reduce hallucinations. It covers use cases like text-to-SQL, classification, RAG and function calling, and is known for running workloads on AMD GPUs.
Train and fine-tune open large language models on your own domain data so output matches your vocabulary, formats and policies.
Tuned inference runtimes and grounding techniques aimed at cutting hallucinations and raising accuracy on domain-specific tasks.
Supports common enterprise patterns — retrieval-augmented generation, text-to-SQL, text classification and function calling.
Run training and inference workloads on AMD GPUs as an alternative GPU supply path for LLM workloads.
Scale is an enterprise AI company that supplies the data, evaluation and deployment layers behind production AI. Its Data Engine sources and labels training data for frontier models, its evaluation work benchmarks model capability, and its platform teams help enterprises and governments move AI systems from pilot into real operations.
Human-sourced and expert-annotated training data, including specialist contributors with advanced degrees, at the quality bar frontier labs require.
Public leaderboards plus private benchmarks that test model capability and safety for the most ambitious AI developers.
Platform and services teams that pick the right use case, build the system and take ownership of the outcome.
Agentic systems designed around measurable business outcomes across private equity portfolios, energy and healthcare operations.


Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all backed by in-house systems research.
Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all backed by in-house systems research.
特化型コンピュータビジョンのデータセットのアノテーションやモデルトレーニングを効率化しますが、一般的なLLMのテキストタスクにはあまり向いていません。
OrcaRouter is an OpenAI-compatible AI gateway that grades every prompt and routes it to the best-value model, then layers on failover, guardrails, an agent firewall, and compliance tooling for production AI.
OrcaRouter is an OpenAI-compatible AI gateway that grades every prompt and routes it to the best-value model, then layers on failover, guardrails, an agent firewall, and compliance tooling for production AI.

Scaleの主要なアノテーション事業と同様に、企業向けのデータラベリングと学習データのキュレーションに特化しています。
特化型エンドツーエンド暗号化の高信頼フロンティア推論

特化型独自のポリシーで統治できる、無制限・OpenAI 互換の LLM API
特化型独自のポリシーで統治できる、無制限・OpenAI 互換の LLM API

企業のマルチモーダルアノテーションやデータ管理ツールを提供しますが、管理されたラベリング作業員への比重は低めです。
企業のマルチモーダルアノテーションやデータ管理ツールを提供しますが、管理されたラベリング作業員への比重は低めです。

特化型一つの接続環境で AI モデルとエージェントを追跡・評価・出荷。

特化型Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation.
特化型Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation.