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35,738 results · Page 370 of 993

sabot

AI agents

Sabot is an open-source benchmark project for evaluating the effectiveness of self-check mechanisms in multi-agent pipelines. It injects controlled faults into reference pipelines built with frameworks such as LangGraph, CrewAI, and AutoGen/Magentic-One, measuring whether the pipelines' own reviewer and guardrail stages can detect, respond to, or miss these faults. Test results show a median detection rate of 16.7%, and by modifying the reviewer prompt to require it to report all inconsistencies, the detection rate can be increased to 55.0%. The project provides frozen measurement specifications, runnable test frameworks, and public raw run traces, and is licensed under Apache-2.0.

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SagaPages

AI images

SagaPages is a free AI storybook generator: users first write a story and save it to their account, then convert it into a printable children's storybook, with consistent character appearance maintained on every page. Signing up gives 20 credits, with no credit card required. Users can upload photos to have the same character appear on every page; after generation, they can preview the entire book online before deciding whether to print. Private by default, with photos controlled by the user. 15 art styles and 15 languages are offered. Credits are shown before generation and are only deducted when a page is successfully generated; after upgrading, clean PDF and HD versions can be exported, and hardcover printing is charged only after the user confirms the order.

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sage

AI agents

SAGE (Sovereign Agent Governed Experience) is an open-source tool that provides persistent project memory for AI agents. It lets agents record project decisions, failed approaches, and useful lessons, and recall relevant context in subsequent sessions, avoiding the need to re-explain project background. SAGE supports MCP-capable clients such as Claude Code, Codex, and Cursor, and developers can integrate it via the Python SDK or a signed REST API. Memories are stored locally by default and managed through the CEREBRUM dashboard, which provides features such as signed provenance, admission lifecycle, access control, confidence adjustment, and deprecation auditing.

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Sail Research

AI developer platforms

Sail Research is a cost-effective API service for open-source large models. It focuses on token-based billing, a $5 monthly free credit, and offers the world's lowest direct API prices for DeepSeek V4.1 Flash (3.3x lower than comparable services in real time, 6x lower asynchronously). The platform is compatible with OpenAI and Anthropic's Responses, Chat Completions, and Messages APIs, enabling rapid migration. Its distinctive Completion Window allows specifying latency tolerance per request, greatly reducing token costs at the same level of intelligence. Sail also supports self-deployed LoRA fine-tuning, RL rollout, and integrates with Tinker, plus Sailboxes full virtual machines for long-running agents. The platform defaults to zero data retention, is pursuing SOC 2 certification, and offers enterprise-grade DPAs, regional data residency, and BAAs.

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Salesloft developer platform

AI coding

The Salesloft Developer Platform is the API and documentation site provided by Salesloft for developers, used to interact with data in its sales platform instances in a RESTful manner. According to the official page information, developers can push, pull, and test integrations, and consult related guides; Salesloft's integrations team can assist in resolving obstacles encountered when accessing data. The platform is positioned as a foundational resource for building sales-related applications, but the page does not provide details such as a specific API list, authentication methods, SDKs, pricing, or usage limits.

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SAM 3D

AI design

SAM 3D is a new-generation AI model in the Segment Anything series, capable of reconstructing three-dimensional objects, people, and scenes from a single image. The product includes two tools, SAM 3D Objects and SAM 3D Body, used respectively for object/scene reconstruction and human pose and body shape estimation. According to the materials, there are already more than 300,000 developers and over 1 million 3D object reconstructions in use. SAM 3D can convert ordinary product photos, scene images, and portraits into exportable 3D assets, supports formats such as GLB, PLY, and OBJ, and provides an HTTP API for integration into applications, tools, and workflows. Its main process is to upload an image, use the segmentation tool to select a target, call SAM 3D for reconstruction, and then download a model that can be used in Blender, Unity, Unreal Engine, and WebGL viewers. It is suitable for scenarios such as e-commerce product displays, game assets, virtual characters, motion analysis, and VR scenes.

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SAM Audio

AI audio

SAM Audio is an independent AI audio separation and sound isolation service built on Meta's Segment Anything Audio Model, allowing users to separate vocals, instruments, speech, and sound effects from complex audio mixes using text, visual, or temporal prompts. The website also provides installation tutorials, model weight acquisition guides, GPU/VRAM requirement explanations, common troubleshooting, and prompt templates and other resources. The website states that it is an independent AI service, is not affiliated with any model provider, and deploys and optimizes Apache-2.0 licensed models on its own infrastructure.

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SambaNova

AI developer platforms

SambaNova is a complete AI platform that provides fast AI inference, fine-tuning, and scalable agentic AI solutions, and can be easily integrated into existing data center infrastructure. At its core is the RDU chip, which uses a dataflow architecture and a three-tier memory design, aiming to achieve energy-efficient, low-cost inference. The platform includes SambaRack hardware (SN40-16, SN50), SambaOrchestrator management software, and an OpenAI-compatible API, supporting bring-your-own checkpoints, automatic scaling, load balancing, and model management. The company claims that SN50 can achieve a six-month return on investment, reduce inference costs by 10x, and require no new data center construction.

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