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AI assistant for teams with secure LLM and company-knowledge access.
Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
Privacy-focused CAPTCHA and bot/fraud-detection service, a drop-in reCAPTCHA alternative for websites and apps.
Enterprise Work AI platform for company-wide search, an AI assistant and building governed agents across 250+ connectors.
Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
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No public pricing
No public pricing
- ✦Unified and safe access to GPT-4
- ✦Connection to team's data for up-to-date answers
- ✦Customizable AI agent building without code
- ✦Team collaboration features for sharing prompts and conversations
- ✦Suggestions for documentation updates and improvements
- ✦LPU custom inference hardware
- ✦GroqCloud tokens-as-a-service API
- ✦High-speed, low-latency inference
- ✦Pay-as-you-go token pricing
- ✦Free API key to start
- ✦Broad open-model support
- ✦AI bot detection
- ✦Transaction fraud protection
- ✦Account-takeover (ATO) defense
- ✦Pull-based SMS MFA
- ✦Private Learning ML risk models
- ✦Two-line reCAPTCHA migration
- ✦Hundreds of integrations
- ✦Enterprise search across company apps
- ✦Personal AI assistant grounded in work data
- ✦Agent builder, orchestration and governance
- ✦250+ connectors and actions
- ✦Enterprise knowledge graph and hybrid search
- ✦Security controls for scaling AI
- ✦Experiment tracking and visualization for ML training runs
- ✦Model and artifact versioning and management
- ✦Hyperparameter optimization tooling
- ✦Collaborative dashboards and reports for ML teams
- ✦LLM application tracing and evaluation tooling
- →RevOps & Sales: Create customer profiles, flag at-risk deals, analyze calls, generate SQL.
- →PMM & Marketing: Write on-brand content, create consistent messaging, translate content, extract insights.
- →Customer Support: Connect to knowledge base, identify product improvements, auto-create FAQs, provide real-time guidance.
- →Product & Design: Improve product copy, analyze customer sentiment, extract competitor insights, generate user stories.
- →Engineering: Review code, auto-create docs, compile incident timelines, generate SQL.
- →Data & Analytics: Enable non-technical teams to query data, automate reporting, transform insights, connect data sources.
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API
- →Blocking bots and spam signups
- →Preventing account takeover
- →Reducing transaction and payment fraud
- →Stopping credential stuffing
- →Search across all company knowledge
- →Answer employee questions with grounded AI
- →Build and deploy custom AI agents
- →Automate cross-system workflows
- →ML engineers tracking and comparing training experiments
- →Research teams versioning datasets and model checkpoints
- →Teams building and evaluating LLM-powered applications
- →Organizations collaborating on machine learning projects