Contextwaise

Contextwaise

GITMORE
Contextwaise Gemini Embedding 2

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Contextwaise:

About

Contextwaise is a context-optimization API and agent SDK for teams building retrieval-augmented generation (RAG) applications, AI agents and other LLM products. It scores retrieved passages, web pages, chat history and tool outputs against the current task, then returns selected context within a token budget before an application calls its language model. A REST API accepts requests from any language; TypeScript and Python SDKs support agent workflows and adapters for the Vercel AI SDK, Anthropic SDK and OpenAI SDK. Results retain the submitted order, and reports show token changes, estimated cost savings and reasons for removals. Contextwaise also provides request logging, configurable budgets and a quality check; its agent SDKs can expose omitted tool-output portions for expansion. Engineering teams can reduce unnecessary model input while retaining their retrieval sources, prompts and model-provider calls.
Gemini Embedding 2:

About

Gemini Embedding models, including the newer Gemini Embedding 2, are part of Google’s Gemini AI ecosystem and are designed to convert text, phrases, sentences, and code into numerical vector representations that capture their semantic meaning. Unlike generative models that produce new content, the embedding model transforms input data into dense vectors that represent meaning in a mathematical format, allowing computers to compare and analyze information based on conceptual similarity rather than exact wording. These embeddings enable applications such as semantic search, recommendation systems, document retrieval, clustering, classification, and retrieval-augmented generation pipelines. The model can process input in more than 100 languages and supports up to 2048 tokens per request, allowing it to embed longer pieces of text or code while maintaining strong contextual understanding.
Contextwaise:

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
Gemini Embedding 2:

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
Contextwaise:

Audience

AI engineers, CTOs and startups building RAG apps, AI agents and other LLM products who want to lower their LLM API costs.
Gemini Embedding 2:

Audience

AI developers and data engineers who need a high-performance embedding model to convert text or code into semantic vectors for search, retrieval, and AI applications
Contextwaise:

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported
Gemini Embedding 2:

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported
Contextwaise:

API

Offers API Supported
Gemini Embedding 2:

API

Offers API Not Supported
Contextwaise:

Screenshots and Videos

No images available
Gemini Embedding 2:

Screenshots and Videos

Contextwaise:

Pricing

$15/month
Free includes 1M context tokens once. Pro is $15/month for 100M tokens/month, then $0.18 per started 1M tokens. Scale is $49/month for 350M tokens/month, then $0.15 per started 1M tokens. Enterprise has custom pricing under an annual contract and offers self-hosted deployment.
Free Version Supported
Free Trial Not Supported
Gemini Embedding 2:

Pricing

Free
Free Version Supported
Free Trial Not Supported
Contextwaise:

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software
Gemini Embedding 2:

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software
Contextwaise:

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported
Gemini Embedding 2:

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported
Contextwaise:

Company Information

GITMORE
Founded: 2026
United Kingdom
contextwaise.com
Gemini Embedding 2:

Company Information

Google
Founded: 1998
United States
blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-embedding-2/
Contextwaise:

Alternatives

Gemini Embedding 2:

Alternatives

Contextwaise:
Gemini Embedding 2:
Contextwaise:
Gemini Embedding 2:
Contextwaise:
Gemini Embedding 2:
Contextwaise:
Synap

Synap

Linkrra LLC
Gemini Embedding 2:
txtai

txtai

NeuML
Contextwaise:

Categories

LLM API Supported
Gemini Embedding 2:

Categories

Embedding Models Supported
Contextwaise:

Integrations

Anthropic Supported
Gemini Not Supported
Gemini Enterprise Not Supported
Gemini platform Not Supported
Google AI Studio Not Supported
Mimasa AI Not Supported
OpenAI Supported
Python Not Supported
Vercel AI SDK Supported
Gemini Embedding 2:

Integrations

Anthropic Not Supported
Gemini Supported
Gemini Enterprise Supported
Gemini platform Supported
Google AI Studio Supported
Mimasa AI Supported
OpenAI Not Supported
Python Supported
Vercel AI SDK Not Supported
Contextwaise:
Claim Contextwaise and update features and information
Claim Contextwaise and update features and information
Gemini Embedding 2:
Claim Gemini Embedding 2 and update features and information
Claim Gemini Embedding 2 and update features and information