Superlinked
A company providing AI inference infrastructure whose product SIE (Superlinked Inference Engine) is used to deploy specialized models to optimize LLM call costs.
Timeline (last 90 days)
Superlinked offers a hosted cluster service that developers can connect to directly without configuring virtual machines themselves.
The Superlinked SDK provides space abstractions such as TextSimilaritySpace and NumberSpace for mapping data of different modalities into vectors, and combines retrieval conditions through Query objects.
When application logic is relatively straightforward and there are high demands for observability and debugging efficiency, native APIs plus lightweight SDKs are often a more pragmatic choice than heavy frameworks.
After the rewrite, the developer chose Superlinked's SDK, saying it is highly readable and directly returns vectors, reranked lists, and extracted entities.
SIE Cloud is run by Superlinked on GPUs, is pay-per-usage, has no idle GPUs, and offers SOC 2 Type 2 certification and US/EU data residency options.
Superlinked's SIE engine supports two deployment modes for the same engine: public filings can be placed on SIE Cloud with pay-per-usage, while customer and internal documents can be self-hosted on your own GPUs, with both sides sharing the same SDK and model IDs.
SIE offers Apache 2.0 open-source weights, with one API covering OCR, extraction, embedding, and reranking.
The SIE self-hosted version is Apache 2.0 licensed, runs in the user's own VPC, is deployed to AWS, GCP, or Azure via Terraform and Helm, and achieves scale-to-zero between tasks on Kubernetes via KEDA.
On SIE Cloud, Qwen3.8-27B (FP8) is offered at $0.72 per million tokens for both input and output; GLiNER2 Large is $0.186 per million input tokens.
Superlinked SIE is an inference layer for task-specific models with three operating modes: SIE Cloud managed (pay-per-use), self-hosted on VPC or Kubernetes (Apache 2.0), and local development.
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All Facts (10)
When application logic is relatively straightforward and there are high demands for observability and debugging efficiency, native APIs plus lightweight SDKs are often a more pragmatic choice than heavy frameworks.
50%UnverifiedSuperlinked offers a hosted cluster service that developers can connect to directly without configuring virtual machines themselves.
50%UnverifiedAfter the rewrite, the developer chose Superlinked's SDK, saying it is highly readable and directly returns vectors, reranked lists, and extracted entities.
50%UnverifiedThe Superlinked SDK provides space abstractions such as TextSimilaritySpace and NumberSpace for mapping data of different modalities into vectors, and combines retrieval conditions through Query objects.
50%UnverifiedThe SIE self-hosted version is Apache 2.0 licensed, runs in the user's own VPC, is deployed to AWS, GCP, or Azure via Terraform and Helm, and achieves scale-to-zero between tasks on Kubernetes via KEDA.
50%UnverifiedSuperlinked's SIE engine supports two deployment modes for the same engine: public filings can be placed on SIE Cloud with pay-per-usage, while customer and internal documents can be self-hosted on your own GPUs, with both sides sharing the same SDK and model IDs.
50%UnverifiedSIE offers Apache 2.0 open-source weights, with one API covering OCR, extraction, embedding, and reranking.
50%UnverifiedSIE Cloud is run by Superlinked on GPUs, is pay-per-usage, has no idle GPUs, and offers SOC 2 Type 2 certification and US/EU data residency options.
50%UnverifiedSuperlinked SIE is an inference layer for task-specific models with three operating modes: SIE Cloud managed (pay-per-use), self-hosted on VPC or Kubernetes (Apache 2.0), and local development.
50%UnverifiedSIE (Superlinked Inference Engine) is an inference engine launched by Superlinked that supports simultaneous deployment of multiple models on a single cluster (multi-model co-location).
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