Alternatives to Parallel Decisions API
Compare Parallel Decisions API alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Parallel Decisions API in 2026. Compare features, ratings, user reviews, pricing, and more from Parallel Decisions API competitors and alternatives in order to make an informed decision for your business.
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1
Lime Connect
Lime Connect (formerly Userlike)
Lime Connect is Germany's leading AI-Agent platform for customer communication. AI Agents automate complete service processes, integrated into your existing systems and developed in Germany for maximum security. All messages from your website, WhatsApp, or any preferred messaging channel are centralized in the Message Center, where professional features such as live translations, file sharing, and video calls enhance customer interactions. Connect AI allows you to deploy autonomous AI Agents that handle up to 70% of customer requests independently, while the AI Copilot assists your service team by summarizing conversations, suggesting answers, and providing relevant knowledge in real time. Automate processes with Workflows, update integrated systems, and deliver seamless support across all channels. Lime Connect is developed and hosted in Germany, making it a GDPR-compliant softwareStarting Price: $87.00 per month -
2
Muse Spark 1.1
Meta
Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs built for agentic tasks, coding, computer use, tool use, and multimodal understanding. The model improves on the original Muse Spark with stronger performance in planning, orchestration, long-context work, coding workflows, and external app interactions. Muse Spark 1.1 can manage a 1 million token context window, remember earlier actions, retrieve important information, compact context, and delegate tasks across parallel subagents. It is designed to operate across tools, MCP servers, custom skills, browsers, native apps, scripts, images, video, PDFs, and audio-based workflows. Developers can access Muse Spark 1.1 through the new Meta Model API public preview, while users can try it in Thinking mode in the Meta AI app and on meta.ai.Starting Price: $1.25 per 1M tokens (input) -
3
Laya AI
Laya AI
Laya AI is an open source family of non-autoregressive System 1 decision models built for fast, typed decisions instead of free-form text generation. Given a state and structured questions, Laya evaluates them in a single forward pass and returns outputs that application code can use directly. It supports three decision types: choice, which selects among named options and returns probabilities; score, which places an input on an ordered rubric such as urgency or severity; and noul, which estimates the probability that a proposition is true. Laya is designed for workloads such as agent and model routing, support ticket triage, guardrails, intent classification, risk and fraud scoring, workflow escalation, RAG filtering, moderation, and phishing detection. It can route requests by department, score urgency, flag refund or churn signals, detect policy or abuse conditions, and escalate uncertain cases to a larger model or human reviewer.Starting Price: Free -
4
OpenAI Decisions API
OpenAI
The Decisions API turns text and images into typed decisions an application can use, evaluating inputs about 10x faster than the Responses API. Developers provide a model, shared input evidence, and one or more questions describing what should be evaluated, and the API returns structured answers that can be used to classify content, route requests, prioritize work, or make threshold-based decisions. It supports three question types: predicate checks whether a condition is true and returns a probability from 0 to 1; choice selects one value from a fixed set and returns option probabilities and confidence; and score evaluates an input against ordered rubric levels and returns a probability-weighted score. Inputs can be plain text or user messages containing both text and images, allowing applications to evaluate cases such as visible product damage, request intent, document type, issue severity, or answer relevance. -
5
DeepSeek-V4-Flash
DeepSeek
DeepSeek-V4-Flash is a high-efficiency Mixture-of-Experts (MoE) language model designed for fast, scalable reasoning and text generation. It features 284 billion total parameters with 13 billion activated parameters, delivering strong performance while optimizing computational cost. The model supports an extensive context window of up to one million tokens, enabling it to process large documents and complex workflows with ease. Its hybrid attention architecture enhances long-context efficiency by reducing memory and compute requirements. Trained on over 32 trillion tokens, DeepSeek-V4-Flash demonstrates solid capabilities across knowledge, reasoning, and coding tasks. It is designed for scenarios where speed and efficiency are critical, offering a balance between performance and resource usage. The model also supports multiple reasoning modes, allowing users to adjust between faster outputs and deeper analysis.Starting Price: $0.14 per 1M tokens (input) -
6
Microsoft-Decision-1
Microsoft
Microsoft-Decision-1 is a fast decision-scoring model built for structured outputs that software can immediately act on. It is designed for routing, classification, prioritization, verification, and workflow control across applications, agents, and automated systems. The model is post-trained from Qwen3.5-9B for single-pass decision scoring and, when given a fixed set of answer options, returns a calibrated probability for each one. It supports yes/no, multiple-choice, rating, and rubric-based grading of AI responses and agent actions through a structured API. Microsoft evaluated the model across 36 benchmarks covering routing, ranking, long context, multilingual and out-of-distribution tasks, reasoning, and safety, and reports that it achieved the highest accuracy in that comparison while also delivering very low latency. The model is also designed for robustness, with testing focused on keeping decisions stable when prompts are paraphrased.Starting Price: $0.042 per 1M tokens -
7
Liquid d1
Liquid AI
d1 is Liquid AI’s first decision model, built to answer structured questions about a situation with probabilities rather than generating text. It takes unstructured data such as text, images, or both, along with one or more questions, processes them in a single forward pass, and returns probabilities without generating output tokens. d1 supports three question types: noul for yes-or-no decisions, choice for selecting among labels with a probability for each option, and score for placing an input on an ordered scale using probability-weighted levels. Multiple questions can be evaluated against the same state in one request, making it useful for real-time decision workflows. Liquid AI demonstrates d1 across applications such as filtering support tickets, browsing code repositories, organizing documents into smart folders, operating websites, compacting agent context, inspecting industrial parts, and playing games from screenshots.Starting Price: Free -
8
Clef
Cloudflare
Clef is a 27B multimodal decision model that turns a state and a schema of typed questions into structured decisions. It can read state information as text, JSON, images, or video and return a probability for every allowed option of every question. The model supports a 65,536-token context window and vision inputs, allowing developers to evaluate both structured application data and visual content in the same decision workflow. Clef supports three typed question formats: noul for estimating the probability that a proposition is true, choice for selecting among predefined options and returning per-option probabilities, and score for evaluating an input against ordered criteria and producing a probability-weighted score. Applications can submit between 1 and 64 questions in a single request, with answers returned under the same question IDs. -
9
Clef-flash
Cloudflare
Clef-flash is a fast 9B multimodal decision model that turns a state and a schema of typed questions into structured decisions. It can read state information as text, JSON, images, or video and returns a probability for every allowed option of every question. The model supports a 24,576-token context window and vision input, allowing developers to evaluate structured application data and visual content within the same workflow. Clef Flash supports three typed question formats: noul for estimating the probability that a proposition is true, choice for selecting among predefined options with per-option probabilities, and score for evaluating an input against ordered criteria and returning a probability-weighted score. Applications can submit from 1 to 64 questions in a single request, with answers returned under the same question IDs. Example uses include deciding whether a support request is urgent, routing it to the correct team, and scoring the severity of customer impact. -
10
Strands Decider
Strands Labs
Strands Decider is a small, fast decision model, or System One model, built for agentic AI workflows. Unlike an LLM that generates arbitrary text, it chooses between predefined options, answers yes-or-no questions, or rates inputs on an ordered scale. Each decision includes calibrated confidence, making it possible to send uncertain cases to a larger model or a human while handling routine decisions quickly. The first model in the family, strands-decider-2B, has 1.9 billion parameters and is based on a Qwen3.5-2B-Base torso with its language-modeling head replaced by a lightweight pointer head. It evaluates answers in one forward pass without text generation or a decoding loop. Supported decision types include choice, noul for probability-of-true questions, and score for ordered scales. The model is designed for tasks such as model routing, tool selection, tool-argument checking, request triage, grounding and safety guardrails, policy classification, and low-cost evaluation.Starting Price: Free -
11
SubQ Snap
Subquadratic
SubQ Snap is a long-context decision model for enterprise and agentic workflows, built to make structured decisions quickly over large amounts of information. It handles tasks such as choosing which files are relevant, selecting the next tool, checking whether a result passes, deciding whether a workflow should continue, and determining when a frontier model is needed. Instead of generating open-ended text, Snap takes context, a question, and a finite set of allowed answers, then returns a probability distribution over those answers. It supports up to 384K tokens of mixed text and image context, allowing it to reason over codebases, contracts, interaction histories, logs, screenshots, charts, diagrams, and scanned pages in a single call. Powered by Subquadratic Sparse Attention, Snap reduces the cost of reading long inputs while a decision head maps contextual representations directly to admissible answers without autoregressive generation.Starting Price: $0.05 per million input tokens -
12
SubQ Snap 1.1
Subquadratic
SubQ Snap is a hosted multimodal decision model for developers building AI agents and enterprise workflows. Through Subquadratic’s API, applications send text or image context with defined questions and receive structured answers such as labels, choices, scores, and probabilities. This supports tasks including tool and file selection, routing, triage, guardrails, ranking, classification, and checking whether a test or result meets specified criteria. The model accepts up to 384K tokens of context and supports image input. It is designed for bounded decisions rather than open-ended text generation, so it can be used alongside a language model that handles planning or writing. Public-preview API documentation includes request examples, model access details, and decision formats.Starting Price: $0.05/1M input tokens -
13
Perplexity Decider
Perplexity
Perplexity Decider is a 27B decision model fine-tuned from Qwen3.8-27B for structured classification and multimodal decision tasks. Rather than generating unrestricted text, it takes an input state and a typed decision schema, then returns the selected result together with calibrated probabilities. The model supports choice decisions for selecting among predefined categories and noul decisions for estimating the probability of a yes-or-no condition. It can also accept images alongside text, allowing applications to make decisions from screenshots or other visual inputs. Example workflows include routing a support request to billing, technical support, or sales, and estimating whether a message expresses urgency. Perplexity reports an overall accuracy of 85.71% across 11 benchmarks, including FinancialPhraseBank, RAGTruth, JudgeBench, TabFact, ContractNLI, Circa, Belebele, and TruthfulQA binary.Starting Price: Free -
14
Perplexity Decisions API
Perplexity
Perplexity’s Decisions API is built for fast, structured decisions that software can use directly. Instead of generating free-form text, it reads natural-language text, JSON, or images as shared state and returns typed answers with probabilities. Developers can attach one or more named questions to the same input and choose among three question types. noul handles yes-or-no judgments and returns the probability of yes from 0 to 1. choice selects from developer-defined options and returns the most likely option, the probability of every option, and a confidence score. score evaluates content against an ordered rubric and returns a probability-weighted score, the full probability distribution, and confidence. The API is designed for tasks such as classification, routing, grading against a rubric, severity assessment, sentiment analysis, or any decision that can be compared against a threshold. -
15
Solar Decide
Upstage
Solar Decide is Upstage’s structured decision model, serving as a System One endpoint on Solar Mini 4. Instead of generating prose, it takes a state together with one or more typed questions and returns a choice, score, or yes/no answer with calibrated probabilities taken directly from the model. Each question is handled in a single forward pass, making the model suited to fast classification, routing, policy checks, prioritization, and other structured decision tasks. The choice type selects among predefined options and returns the selected option, individual probabilities, and confidence. The score type evaluates an input against ordered criteria and returns a probability-weighted score, legend, probability distribution, and confidence. The noul type returns the probability that a yes-or-no proposition is true. Multiple questions can share the same state in one request, and the state can be provided as text or any JSON value serialized into the prompt.Starting Price: $0.1 per 1M tokens -
16
Span-01
Respan
Span-01 is a hyper-parallel reasoning classifier built to detect complex behaviors across long production traces in a single forward pass. Rather than generating tokens sequentially, it reasons over natural-language behavior definitions and returns direct probabilities for present, absent, and not_observable. The model is trained for general classification reasoning with RLAIF before being specialized for behavior detection, allowing it to apply previously unseen definitions to new behaviors and domains instead of relying on a fixed taxonomy. At inference time, hyper-parallel definition branches evaluate multiple behaviors against the same trace context simultaneously, while hybrid attention helps preserve reasoning over long, complex inputs. Span-01 is designed for production monitoring across safety, reliability, grounding, agent behavior, and response quality, including jailbreak and prompt injection detection, privacy, and secrets.Starting Price: $199 per month -
17
Tev1
Together AI
Tev1 is a fast decision and classification model built by Together AI and fine-tuned from Qwen3.5 4B. It is designed around a simple interface: provide a piece of state, a question, and 2 to 24 labeled options, and the model returns exactly one letter that software can map back to a semantic key. This structure supports production tasks such as routing support tickets, evaluating automated returns, applying policy rules, rating sentiment, categorizing documents, and inserting deterministic decision points into larger agent pipelines. The model has 4.7B parameters, a 32.8K-token context window, and runs with non-thinking generation for fast, predictable classification. It was trained on 37,840 examples spanning intent detection, boolean comprehension, sentiment, policy application, routing, news categories, and research-paper taxonomy. Recommended settings use temperature 0 and a very small output budget so responses remain stable and easy to parse.Starting Price: $0.04 per 1M tokens -
18
Jev
TypeSafe AI
Jev is a System One Model from TypeSafe AI designed for fast, structured decision-making inside software and automated workflows. Unlike conventional large language models that generate free-form text token by token, Jev accepts unstructured state and returns predefined type-safe values with calibrated probabilities and confidence scores. The model uses a parallel sampling architecture and a training approach called Reinforcement Learning for Calibrated Decisions, which is optimized for producing reliable probabilistic decisions rather than conversational responses. Jev is intended for tasks such as classification, routing, scoring, extraction, branching logic, verification, guardrails, and other AI-powered workflows where structured outputs can plug directly into application code. TypeSafe reports end-to-end response times ranging from about 70 to 500 milliseconds and says Jev can be substantially faster and more efficient than frontier language models on System One-style workloads.Starting Price: Input: $0.042 / 1M tokens -
19
DecisionsApi
DecisionsApi
DecisionsApi is a developer-focused AI platform for testing decision models in an online playground and integrating them through an API. Developers provide text, JSON objects, or arrays of text as state, define typed Choice, Score, or Noul (yes/no) questions, and receive structured answers with probabilities, confidence, usage, and request details. The platform supports customer-request routing, agent next-step selection, evidence checks, safety gates, and human-review workflows, with API key management, usage history, and one shared credit balance across the playground and API.Starting Price: $10 -
20
scribe
scribe
scribe is a self-hosted knowledge base written automatically by your tools. It reads Git history, Claude Code and Codex sessions, self-sent URLs, and drop files, then turns that work into a curated, cross-project wiki of plain Markdown stored in Git. Instead of making developers maintain a second brain or rebuild context whenever an agent session starts from zero, scribe captures decisions, fixes, evaluations, and the reasoning behind them so agents can query that memory before they act. Its pipeline runs on cron: it discovers projects, filters low-value noise with FTS5 before invoking an LLM, extracts grounded facts through bounded and two-pass workflows, and compiles them into entity-first pages with YAML frontmatter, wikilinks, backlinks, retrieval context, and typed relationships such as supersedes, contradicts, derived_from, specializes, and extends. -
21
TASKIN
SoftLab
TASKIN is developing a shared workspace for people and AI agents to keep work requests connected to their sources, owners, context, acceptance criteria, reviews and outcomes. Its product direction includes carrying relevant context between conversations, preparing bounded work for agents, making results reviewable by people, and keeping open questions visible. Example workflows show a human owner, an agent preparing a draft and a reviewer checking evidence before a decision. The public site currently presents fictional illustrations rather than a live workspace: it does not connect accounts, run agents or accept payments. Connected mail, planning, native experiences and broader context continuity are described as in development or future concepts, with availability and release timing not confirmed. It is aimed at founders, operators and teams coordinating work across people and AI tools. -
22
TwitterAPIs
TwitterAPIs
TwitterAPIs is a hosted Twitter/X data API for developers, researchers, data teams, and AI agent builders. REST endpoints support post search, tweet details and threads, user profiles and timelines, followers, following, lists, and trends. The API uses bearer-key authentication, returns JSON, and provides an OpenAPI specification and endpoint documentation. Users can connect it to MCP-compatible assistants through its MCP server or call it from automation platforms using HTTP. Linked-account endpoints also support actions such as posting, liking, and following. Standard reads are billed per request, with higher rates for some endpoints; new accounts receive usage credits. TwitterAPIs is an independent third-party service, not affiliated with X. It supports application development, social data collection, monitoring, and AI-agent workflows requiring X data without an X developer account.Starting Price: $0.0008/call -
23
Mistral OCR 4
Mistral AI
Mistral OCR 4 is a document extraction and understanding model built for enterprise search, RAG, domain-specific retrieval pipelines, and production-grade document intelligence. It extracts and structures content from a wide range of documents, moving beyond clean text and tables to return a structured representation of each page. Alongside extracted text, OCR 4 provides bounding boxes, typed-block classification, and inline confidence scores, helping downstream systems understand not only what the document says, but where each element sits, what role it plays, and how confident the model is in each region. Bounding boxes make in-context highlighting and reliable data pipelines possible, while block types and confidence scores support source-grounded citations, redactions, and human-in-the-loop verification. OCR 4 accepts common enterprise formats, including PDF, DOC, PPT, and OpenDocument, and supports 170 languages across 10 language groups.Starting Price: $2 per 1000 pages -
24
Gram
Speakeasy
Gram is an open source platform that enables developers to create, curate, and host Model Context Protocol (MCP) servers effortlessly, by transforming REST APIs (via OpenAPI specs) into AI-agent-ready tools without code changes. It guides users through a workflow: generating default tooling from API endpoints, scoping down to relevant tools, composing higher-order custom tools by chaining multiple calls, enriching tools with contextual prompts and metadata, and instantly testing within an interactive playground. With built-in support for OAuth 2.1 (including Dynamic Client Registration or user-authored flows), it ensures secure agent access. Once ready, these tools can be hosted as production-grade MCP servers, complete with centralized management, role-based access, audit logs, and compliance-ready infrastructure, including Cloudflare edge deployment and DXT-packaged installers for easy distribution.Starting Price: $250 per month -
25
Caterfli
Caterfli
Caterfli is a hosted AI-agent platform that connects to PostgreSQL or MySQL databases, REST APIs, OpenAPI services, and MCP servers. It discovers available tables, endpoints, and tools, then drafts agents that users can review and configure. Teams can ask questions or request actions in natural language through web chat; Telegram, Slack, and WhatsApp access is available on eligible plans. Agents can read data, create or update records, run reports, and delegate work to other agents. Workspace roles and permissions limit available actions, and policy checks validate each tool call and its arguments. Destructive or high-risk operations can pause for human approval. Execution traces and change histories support review. Caterfli is for teams seeking a conversational interface to existing business systems without migrating their data. A free plan includes one connection and one agent, with paid plans offering higher limits and additional features.Starting Price: $19/mo -
26
ScraperSocial
ScraperSocial
ScraperSocial is a hosted REST API and MCP server that returns publicly available social, video, commerce, review, search, and developer-source data as JSON. Developers, data teams, marketers, researchers, and AI-agent builders can use it to retrieve public profiles, posts, channel and engagement statistics, comments, keyword and hashtag results, reviews, trending items, video transcripts, and summaries from supported platforms. The API offers documented endpoints with a shared response format, API-key authentication, and endpoint-specific credit usage; its MCP server exposes tools for agent clients. Common uses include social listening, creator and influencer research, market research, content analysis, and feeding public-source information into applications, analytics pipelines, and AI workflows. The service is delivered online, with API documentation and an OpenAPI specification.Starting Price: $5/month -
27
Oz
Warp
Oz is a cloud-based orchestration platform for AI coding agents that lets developers and teams run, manage, automate, and scale unlimited parallel cloud coding agents without building custom infrastructure, providing programmable, auditable, and fully steerable workflows that automate repetitive development tasks and complex code changes. It enables you to launch agents from the CLI, web app, APIs, SDKs, Warp Terminal, or even mobile, orchestrate hundreds of agents in parallel with built-in audit trails, session tracking, and visibility, and monitor or interact with running agents in a shared control plane. Oz supports flexible hosting on your infrastructure or Warp’s, isolates each agent in secure environments, produces real artifacts like plans and pull requests, and handles multi-repo changes so agents can coordinate sweeping updates across large codebases.Starting Price: $18 per month -
28
WordCraft
ArtCraft
WordCraft is a free, open-source word processor for people who write and format documents. Its ribbon interface provides editing and page-design tools for styles, tables, images, citations, footnotes, tables of contents, comments, and tracked changes, along with spelling and grammar checks and mail merge. It reads and writes DOCX, opens older DOC files, works with ODT, RTF, HTML, Markdown, LaTeX, and plain text, and exports PDF and page images. WordCraft runs as a native application on Windows, macOS, and Linux, and also has a WebAssembly edition that can be hosted on a static server. Its command-line tools, JSON control channel, and Model Context Protocol server support scripted and AI-agent document workflows. The software is in alpha, so file compatibility and feature coverage continue to develop.Starting Price: $0 -
29
OpenAI Agents API
OpenAI
The Agents API lets developers build and run cloud agents with the same harness and infrastructure that powers Codex, fully managed by OpenAI. A production-ready agent can be created with a single API call by specifying the task, model, tools, and environment, while OpenAI hosts and maintains the agent harness. Developers can choose where agents run: in an OpenAI-hosted sandbox, on their own infrastructure, or through supported sandbox partners. OpenAI-hosted sandboxes provide secure environments where agents can run code, work with files, use packages, skills, and plugins, and produce artifacts. The API is designed for long-running work, with automatic context compaction that preserves relevant information as sessions span multiple context windows. Tool search loads relevant tool definitions only when needed, while programmatic tool calling lets agents run calls in parallel, chain related operations, and filter or combine results in code. -
30
Parallel
Parallel
The Parallel Search API is a web-search tool engineered specifically for AI agents, designed from the ground up to provide the most information-dense, token-efficient context for large-language models and automated workflows. Unlike traditional search engines optimized for human browsing, this API supports declarative semantic objectives, allowing agents to specify what they want rather than merely keywords. It returns ranked URLs and compressed excerpts tailored for model context windows, enabling higher accuracy, fewer search steps, and lower token cost per result. Its infrastructure includes a proprietary crawler, live-index updates, freshness policies, domain-filtering controls, and SOC 2 Type 2 security compliance. The API is built to fit seamlessly within agent workflows: developers can control parameters like maximum characters per result, select custom processors, adjust output size, and orchestrate retrieval directly into AI reasoning pipelines.Starting Price: $5 per 1,000 requests -
31
Glasser
Super Intent
Glasser is a data API marketplace for AI agents and developers. It brings specialist data providers into one account and balance, with sources for company and people research, search and SEO, finance, property, jobs, social media, and product data. Users can discover endpoints, inspect inputs and prices before a call, then retrieve data through Glasser's hosted service, a Model Context Protocol (MCP) connection, command-line tool, or agent setup skill. Charges apply per data call rather than as a monthly Glasser subscription; rates vary by provider and endpoint. Glasser supports agent workflows needing structured external data for research, lead generation, enrichment, analysis, or search. Users choose which endpoint to call and can review results and charges in the workspace. Endpoint search and price checks are free, and new accounts receive a $1 credit for paid calls. -
32
Reason
Reason
Reason is an autonomous software engineer and AI coding agent designed to take ownership of real engineering work, from researching codebases and fixing bugs to implementing features and verifying results. It works across connected repositories, local computers, and cloud environments, allowing developers to delegate tasks without interrupting their workflows. The agent can explore codebases, trace call paths, reproduce failures, edit files, run tests, and produce verified pull requests for human review. Its research capabilities provide evidence-backed findings with citations linking directly to source files and lines, while repository memory preserves knowledge for future sessions. Reason supports parallel subagents, isolated workspaces, scheduled sessions, and automated workflows for development and operations. Teams can connect repositories, manage permissions, inspect code changes, and review builds, regression tests, and deployment checks before merging. -
33
Rippit
Rippit
Rippit is a conversation data platform that turns customer interactions from helpdesks, sales calls, meetings and other connected sources into structured, searchable data. Customer experience, support, product, sales and operations teams can use natural-language analyses and reusable AI agents to identify contact drivers, product feedback, churn signals, quality issues, compliance concerns and chatbot or AI-agent problems. The platform enriches conversation records with fields such as intent, sentiment, resolution and root cause, then helps teams examine trends and trace findings to source conversations. Teams can schedule Agent Apps to repeat analyses and deliver insights, and connect external assistants through Rippit’s hosted Model Context Protocol server. It helps organizations analyze customer conversations and turn findings into team workflows.Starting Price: $185/month -
34
runx
0state
runx is an open-source runtime and command-line tool for creating, discovering, and executing governed skills for AI agents. Developers can define bounded workflows, grant specific credentials and permissions, and run skills locally with their own provider accounts. Runs can pause for approval or missing input, then resume while retaining a signed receipt that can be inspected and verified. Skills can be installed from a public registry and used with compatible agents such as Claude Code, Cursor, and Codex. An optional hosted service adds managed OAuth connections, scoped grants, API-based run submission and inspection, approval handling, and receipt notarization. The CLI can also operate locally or in a self-hosted environment. runx is intended for developers and platform teams building and operating AI-agent workflows that need explicit authority boundaries and auditable execution.Starting Price: $0 -
35
ADE
ADE
ADE is an agentic development environment for software developers who use AI coding agents with Git repositories. It organizes parallel tasks in isolated Git worktrees and combines agent chat, multi-agent sessions, terminals, file editing, testing, browser-based QA, automation, and pull-request review in one workspace. Desktop, browser, terminal, and iOS clients sync project activity through an ADE Brain running on a machine you control; Linux can host the Brain without a Linux desktop app. ADE supports Claude Code, Codex, Cursor, Factory Droid, and OpenCode, and connects to GitHub and Linear for pull requests and issue workflows. Developers can review changes, inspect test results, and continue work across devices.Starting Price: $0 -
36
FineData.ai
Finedata
FineData.ai is a hosted web-scraping API and MCP server for developers and AI-agent workflows that need data from public or authorized web pages. Send a URL through REST or an MCP client to retrieve page content as Markdown, text, links, screenshots, or raw HTML, or request structured JSON using selectors, a JSON schema, or an extraction prompt. Optional browser rendering, proxy routing, country targeting, CAPTCHA handling, asynchronous jobs, and batch requests support pages and collection tasks with differing requirements. Documented use cases include price and catalog monitoring, property listings, market research, lead generation, and search-results tracking for users’ own domains. Usage is metered in tokens; failed scrapes are not billed. The API supports Python, JavaScript, and standard HTTP clients, while the MCP server connects with clients such as Cursor and Claude Desktop.Starting Price: $47/month -
37
OpenEvidence
OpenEvidence
OpenEvidence is an AI-powered clinical decision support platform designed for verified health care professionals, which aggregates, synthesizes, and visualizes peer-reviewed medical evidence to answer point-of-care questions rapidly and reliably. The system covers over 160 specialties and more than 1,000 diseases or therapeutic areas, presenting results grounded in high-quality sources such as JAMA, NEJM, and clinical guidelines. It supports a deep, intuitive search interface that returns evidence-based answers in 5–10 seconds, always with citations, and ensures transparency by surfacing the references behind each answer. In addition to search, OpenEvidence includes features like “Visits,” a module that transcribes patient encounters, enriches documentation with clinical intelligence, drafts notes, and integrates assessment and plan guidance into clinician workflows.Starting Price: Free -
38
NeuralVerge
NeuralVerge Inc.
NeuralVerge is an AI research and data extraction platform for go-to-market, research and compliance teams, and for the AI agents they build. Ask a question in plain language or point it at a company, a person or a URL, and get back a structured answer with the source behind every field. AI Research plans the question into sub-queries, routes them to the right sources in parallel, extracts the fields and reconciles the findings into one cited answer. AI Extract turns any page or document into clean JSON in the schema you define, with no selectors to maintain. 29 data sources sit behind one request format: company intelligence, 12 corporate registries, contact enrichment and public social profiles. Everything is available in a web app, over a REST API and as an MCP server, so analysts and agents share the same pipeline. Pricing is points-based, from $20 per month, with no per-seat fees. No credit card is needed to try a request.Starting Price: $20/month -
39
Reflexio
Reflexio
Reflexio is an AI-agent learning platform for developers building and operating agents. It ingests agent interactions, execution traces, tool calls, and user corrections through an SDK, REST API, CLI, or supported tracing-platform connections, then extracts recurring failures into reusable playbooks and user profiles. At runtime, an agent can retrieve relevant learned guidance before responding. The Hosted Enterprise portal lets teams inspect, edit, approve, reject, search, and evaluate learnings. Reflexio helps agents apply corrections across interactions without changing model weights. Teams can use the managed cloud service, configure their own model-provider keys, or self-host in AWS, Google Cloud, or Azure. Enterprise trace imports are available from Braintrust, Langfuse Cloud, and LangSmith Cloud; Reflexio also provides a mem0 wrapper and an OpenClaw integration.Starting Price: $0/month -
40
Zof
Zof AI, Inc.
Zof connects software changes to their potential impact, required verification and supporting evidence so engineering teams can review production decisions. The platform brings together system context, verification, evidence and policy-based controls for AI-assisted software delivery. Capabilities, usage allowances and deployment arrangements vary by plan. Enterprise and secure deployment options require further architecture and agreement review. Zof Tools is a separate hosted diagnostics offering, with focused website, code and API checks. Tools has bounded free previews and separately priced paid runs and recurring options. Those prices do not represent the main Zof platform plans.Starting Price: $1,990/year -
41
DailyHelm
DailyHelm
DailyHelm is an agentic AI business reviewer that monitors a company’s analytics, ads, SEO, store, codebase, and costs overnight, then delivers a prioritized list of what changed, why it matters, and what to fix next. Instead of requiring users to check multiple dashboards and interpret metrics themselves, six specialist agents review different areas of the business in parallel while Aria, the lead agent, correlates their findings, removes duplicates, and ranks issues by expected revenue impact. Iris monitors analytics and growth signals, Pitch reviews ad spend and performance, Echo tracks SEO and indexation, Ada investigates code and deployment health, Penny monitors billing and costs, and Sage checks site UX and conversion blockers. Every finding includes supporting evidence, an impact score, confidence level, effort estimate, and a recommended action. Aria can also answer questions about the business using its profile, current findings, and recent metrics as live context.Starting Price: $99 per month -
42
7AI
7AI
7AI is an agentic security platform built to automate and accelerate the entire security operations lifecycle using specialized AI agents that investigate security alerts, form conclusions, and take action, turning processes that once took hours into minutes. Unlike traditional automation tools or AI copilots, 7AI deploys purpose-built, context-aware agents that are architecturally bounded to avoid hallucinations, and operate autonomously; they ingest alerts from existing security tools, enrich and correlate data across endpoints, cloud, identity, email, network, and more, and then produce full investigations with evidence, narrative summaries, cross-alert correlation, and audit trails. It offers a complete security stack: detection to triage alerts (filtering out noise and up to 95–99% of false positives), investigations (multi-system data-gathering and expert-level reasoning), and unified incident-case management (auto-populated cases, team collaboration, and handoffs). -
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Redditapis
Redditapis
Redditapis is a hosted REST API for developers and data teams that need programmatic access to Reddit content and account actions. With a bearer token, applications can retrieve subreddit listings, posts, comments, comment trees, search results, community details and user profiles, and can submit posts or comments, vote, or send direct messages through supported endpoints. The service also offers keyword and subreddit monitoring, with alerts delivered to webhooks, Slack or Discord. An optional MCP server exposes search, post, comment and user tools to compatible AI clients and agent frameworks. Typical uses include application integrations, research workflows, market and brand monitoring, and supplying Reddit context to AI agents. API calls are billed per request; monthly read-volume and monitoring plans are also available. Redditapis is an independent third-party service, not Reddit's own API.Starting Price: $0.0015/call -
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The MCP Census
MCP Census
The MCP Census is a web-based evidence-checking service for developers and teams that use Model Context Protocol (MCP) servers. It compares server listings with public signals such as repository identity and status, package availability, hosted endpoint health, registry records, and vulnerability advisories. Users can look up a server or submit an MCP configuration and receive PASS, REVIEW, BLOCK, or UNKNOWN results under a versioned policy, with reasons and supporting evidence. The service is accessible through a website, REST API, and remote MCP server, and can be used in agent workflows and CI checks for configuration changes. Setup guides connect it to coding agents and developer tools. MCP Census is an initial public-evidence gate, not a malware scanner, penetration test, or guarantee that a server is safe to run.Starting Price: $0 -
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HeyBrain
HeyBrain
HeyBrain is an AI-powered knowledge management platform that helps organizations centralize company information and make it accessible to employees and AI agents. The platform provides a shared knowledge layer for organizing documents, project context, business decisions, and reusable instructions. Its AI memory capabilities allow compatible AI assistants to retrieve relevant information across conversations and workflows without repeatedly providing the same background. HeyBrain supports document uploads, knowledge connections with Google Drive and Notion, and integration with AI tools through the Model Context Protocol (MCP). Its governance capabilities help organizations manage access to shared information, define agent permissions, and review source evidence behind AI-generated answers. The platform is designed to support enterprise knowledge retrieval, AI agent development, team collaboration, and secure information sharing across business applications.Starting Price: $30/month -
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Aigency
Aigency
Aigency is an agentic commerce platform. We host a parallel, agentic version of your store on your own domain (ai-yourbrand-com) that receives the shoppers AI assistants like ChatGPT, Gemini, Claude, and Perplexity send you. Instead of a static page, that traffic lands in a conversation that answers the product, price, and fit questions shoppers and AIs actually ask, with a working path to buy, and checkout stays on your site, on your terms. Under the hood it is a system of agents that crawl, structure, render, monitor, and transact, running off-site in parallel to your store: no re-platform, no migration, live in days. A control and policy engine sets the rules for what the agents can recommend, what they must never say, and where they route shoppers. Every question the agent answers becomes demand data you never see inside ChatGPT. The entry point is a free scan at aigency.ai that shows where ChatGPT is already sending your traffic and what those shoppers land on. -
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Oracle AI Agent Platform
Oracle
Oracle AI Agent Platform is a fully-managed service that enables the creation, deployment, and management of intelligent virtual agents powered by large language models and integrated AI technologies. Agents can be set up through a simple few-step process, and can orchestrate tools such as natural‐language-to‐SQL conversion, retrieval-augmented generation from enterprise knowledge bases, custom function or API calling, and even the ability to coordinate sub-agents. They support multi-turn conversational experiences with context retention across sessions, enabling agents to handle follow‐up questions and maintain personalised, consistent interactions. Built-in guardrails help enforce content moderation, prompt-injection prevention, and protection of PII (personally identifiable information), while optional human-in-the-loop workflows allow real-time supervision and escalation.Starting Price: $0.003 per 10,000 transactions -
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Grounded Language Model (GLM)
Contextual AI
Contextual AI introduces its Grounded Language Model (GLM), engineered specifically to minimize hallucinations and deliver highly accurate, source-based responses for retrieval-augmented generation (RAG) and agentic applications. The GLM prioritizes faithfulness to the provided data, ensuring responses are grounded in specific knowledge sources and backed by inline citations. With state-of-the-art performance on the FACTS groundedness benchmark, the GLM outperforms other foundation models in scenarios requiring high accuracy and reliability. The model is designed for enterprise use cases like customer service, finance, and engineering, where trustworthy and precise responses are critical to minimizing risks and improving decision-making. -
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Meta Model API
Meta
Meta Model API is a new developer API for building with Muse Spark 1.1, Meta’s multimodal reasoning model built for agentic tasks, coding, tool use, computer use, and multimodal understanding. Now in public preview, it gives developers a way to access Muse Spark 1.1 through an OpenAI-compatible package, making it easier to point existing clients at the API, keep the same code structure, and set the model to muse-spark-1.1. Muse Spark 1.1 is designed for personal agentic tasks that require planning and orchestration across external apps and services, with the ability to generalize to new native tools, MCP servers, and custom skills. As a main agent, it can gather context, make a plan, and delegate execution across parallel subagents; as a subagent, it follows its role, understands available tools, and knows when to escalate back. The model can actively manage a 1 million-token context window, remember actions, retrieve information from much earlier work, and compact context.Starting Price: $1.25 per 1M tokens -
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SenseLab
SenseLab
SenseLab is a cloud-based memory and learning layer for AI agents and agent-driven applications. It provides shared knowledge spaces (“Rooms”) where agents and teams can record, retrieve, and share context across sessions, models, and tools. Agents can store findings, decision context, and outcomes; the service maintains versioned records and uses outcome feedback to adjust confidence in knowledge. SenseLab provides an MCP server and Python and TypeScript SDKs for connecting agent clients and applications through API-key access. Teams can use it to carry context between agents, coordinate work, review decision histories, and retain structured traces for evaluation or model-training workflows. It is intended for developers and organizations building systems with multiple AI agents. The vendor also documents a self-hosting option through its open-source codebase.Starting Price: $29/month
