Alternatives to AfterQuery
Compare AfterQuery alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to AfterQuery in 2026. Compare features, ratings, user reviews, pricing, and more from AfterQuery competitors and alternatives in order to make an informed decision for your business.
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1
OORT DataHub
OORT DataHub
Data Collection and Labeling for AI Innovation. Transform your AI development with our decentralized platform that connects you to worldwide data contributors. We combine global crowdsourcing with blockchain verification to deliver diverse, traceable datasets. Global Network: Ensure AI models are trained on data that reflects diverse perspectives, reducing bias, and enhancing inclusivity. Distributed and Transparent: Every piece of data is timestamped for provenance stored securely stored in the OORT cloud , and verified for integrity, creating a trustless ecosystem. Ethical and Responsible AI Development: Ensure contributors retain autonomy with data ownership while making their data available for AI innovation in a transparent, fair, and secure environment Quality Assured: Human verification ensures data meets rigorous standards Access diverse data at scale. Verify data integrity. Get human-validated datasets for AI. Reduce costs while maintaining quality. Scale globally. -
2
Bitext
Bitext
Bitext provides multilingual, hybrid synthetic training datasets specifically designed for intent detection and LLM fine‑tuning. These datasets blend large-scale synthetic text generation with expert curation and linguistic annotation, covering lexical, syntactic, semantic, register, and stylistic variation, to enhance conversational models’ understanding, accuracy, and domain adaptation. For example, their open source customer‑support dataset features ~27,000 question–answer pairs (≈3.57 million tokens), 27 intents across 10 categories, 30 entity types, and 12 language‑generation tags, all anonymized to comply with privacy, bias, and anti‑hallucination standards. Bitext also offers vertical-specific datasets (e.g., travel, banking) and supports over 20 industries in multiple languages with more than 95% accuracy. Their hybrid approach ensures scalable, multilingual training data, privacy-compliant, bias-mitigated, and ready for seamless LLM improvement and deployment.Starting Price: Free -
3
Phi-4-reasoning
Microsoft
Phi-4-reasoning is a 14-billion parameter transformer-based language model optimized for complex reasoning tasks, including math, coding, algorithmic problem solving, and planning. Trained via supervised fine-tuning of Phi-4 on carefully curated "teachable" prompts and reasoning demonstrations generated using o3-mini, it generates detailed reasoning chains that effectively leverage inference-time compute. Phi-4-reasoning incorporates outcome-based reinforcement learning to produce longer reasoning traces. It outperforms significantly larger open-weight models such as DeepSeek-R1-Distill-Llama-70B and approaches the performance levels of the full DeepSeek-R1 model across a wide range of reasoning tasks. Phi-4-reasoning is designed for environments with constrained computing or latency. Fine-tuned with synthetic data generated by DeepSeek-R1, it provides high-quality, step-by-step problem solving. -
4
Step 3.5 Flash
StepFun
Step 3.5 Flash is an advanced open source foundation language model engineered for frontier reasoning and agentic capabilities with exceptional efficiency, built on a sparse Mixture of Experts (MoE) architecture that selectively activates only about 11 billion of its ~196 billion parameters per token to deliver high-density intelligence and real-time responsiveness. Its 3-way Multi-Token Prediction (MTP-3) enables generation throughput in the hundreds of tokens per second for complex multi-step reasoning chains and task execution, and it supports efficient long contexts with a hybrid sliding window attention approach that reduces computational overhead across large datasets or codebases. It demonstrates robust performance on benchmarks for reasoning, coding, and agentic tasks, rivaling or exceeding many larger proprietary models, and includes a scalable reinforcement learning framework for consistent self-improvement.Starting Price: Free -
5
Gramosynth
Rightsify
Gramosynth is a powerful AI-driven platform for generating high-quality synthetic music datasets tailored for training next-gen AI models. Leveraging Rightsify’s vast corpus, the system operates on a perpetual data flywheel that continuously ingests freshly released music to generate realistic, copyright-safe audio at professional 48 kHz stereo quality. Datasets include rich, ground-truth metadata such as instrument, genre, tempo, key, and more, structured specifically for advanced model training. It accelerates data collection timelines by up to 99.9%, eliminates licensing bottlenecks, and supports virtually limitless scaling. Integration is seamless via a simple API that allows users to define parameters like genre, mood, instruments, duration, and stems, producing fully annotated datasets with unprocessed stems, FLAC audio, alongside outputs in JSON or CSV formats. -
6
Twine AI
Twine AI
Twine AI offers tailored speech, image, and video data collection and annotation services, including off‑the‑shelf and custom datasets, for training and fine‑tuning AI/ML models. It offers audio (voice recordings, transcription across 163+ languages and dialects), image and video (biometrics, object/scene detection, drone/satellite feeds), text, and synthetic data. Leveraging a vetted global crowd of 400,000–500,000 contributors, Twine ensures ethical, consent‑based collection and bias reduction with ISO 27001-level security and GDPR compliance. Projects are managed end‑to‑end through technical scoping, proofs of concept, and full delivery supported by dedicated project managers, version control, QA workflows, and secure payments across 190+ countries. Its service includes humans‑in‑the‑loop annotation, RLHF techniques, dataset versioning, audit trails, and full dataset management, enabling scalable, context‑rich training data for advanced computer vision. -
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DataGen
DataGen
DataGen is a leading AI platform specializing in synthetic data generation and custom generative AI models for machine learning projects. Their flagship product, SynthEngyne, supports multi-format data generation including text, images, tabular, and time-series data, ensuring privacy-compliant, high-quality training datasets. The platform offers scalable, real-time processing and advanced quality controls like deduplication to maintain dataset fidelity. DataGen also provides professional AI development services such as model deployment, fine-tuning, synthetic data consulting, and intelligent automation systems. With flexible pricing plans ranging from free tiers for individuals to custom enterprise solutions, DataGen caters to a wide range of users. Their solutions serve diverse industries including healthcare, finance, automotive, and retail. -
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DataSeeds.AI
DataSeeds.AI
DataSeeds.ai provides large‑scale, ethically sourced, high‑quality image (and video) datasets tailored for AI training, combining both off‑the‑shelf collections and on‑demand custom builds. Their ready‑to‑use photo sets include millions of images fully annotated with EXIF metadata, content labels, bounding boxes, expert aesthetic scores, scene context, pixel‑level masks, and more. It supports object and scene detection tasks, global coverage, and human‑peer‑ranking for label accuracy. Custom datasets can be launched rapidly via a global contributor network in 160+ countries, collecting images that align with specific technical or thematic requirements. Accompanying annotations include descriptive titles, detailed scene context, camera settings (type, model, lens, exposure, ISO), environmental attributes, and optional geo/contextual tags. -
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Dataocean AI
Dataocean AI
DataOcean AI is a leading provider of high-quality, labeled training data and comprehensive AI data solutions, offering over 1,600 off‑the‑shelf datasets and thousands of customized datasets for machine learning and AI applications. Dataocean's offerings cover diverse modalities (speech, text, image, audio, video, multimodal) and support tasks such as ASR, TTS, NLP, OCR, computer vision, content moderation, machine translation, lexicon development, autonomous driving, and LLM fine‑tuning. It combines AI-driven techniques with human-in-the-loop (HITL) processes via their DOTS platform, which includes over 200 data-processing algorithms and hundreds of labeling tools for automation, assisted labeling, collection, cleaning, annotation, training, and model evaluation. With almost 20 years of experience and presence in more than 70 countries, DataOcean AI ensures strong quality, security, and compliance, serving over 1,000 enterprises and academic institutions globally. -
10
Synetic
Synetic
Synetic AI is a platform that accelerates the creation and deployment of real-world computer vision models by automatically generating photorealistic synthetic training datasets with pixel-perfect annotations and no manual labeling required, using advanced physics-based rendering and simulation to eliminate the traditional gap between synthetic and real-world data and achieve superior model performance. Its synthetic data has been independently validated to outperform real-world datasets by an average of 34% in generalization and recall, covering unlimited variations like lighting, weather, camera angles, and edge cases with comprehensive metadata, annotations, and multi-modal sensor support, enabling teams to iterate instantly and train models faster and cheaper than traditional approaches; Synetic AI supports common architectures and export formats, handles edge deployment and monitoring, and can deliver full datasets in about a week and custom trained models in a few weeks. -
11
Luel
Luel
Luel is a two-sided AI training data marketplace that connects enterprises and AI teams with a global network of contributors to source, license, and generate high-quality multimodal datasets for machine learning models. It provides curated, rights-cleared datasets that are verified, structured, and ready for training, including video, audio, and image data tailored for use cases such as speech recognition, computer vision, and multimodal AI systems. It enables companies to either browse a catalog of existing datasets or request custom data collection campaigns by specifying detailed requirements such as format, labels, quality standards, and scenarios, which are then fulfilled through a vetted contributor network. Submissions undergo multi-stage validation and quality checks to ensure compliance, accuracy, and usability, delivering enterprise-ready datasets with full licensing and documentation. -
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Appen
Appen
The Appen platform combines human intelligence from over one million people all over the world with cutting-edge models to create the highest-quality training data for your ML projects. Upload your data to our platform and we provide the annotations, judgments, and labels you need to create accurate ground truth for your models. High-quality data annotation is key for training any AI/ML model successfully. After all, this is how your model learns what judgments it should be making. Our platform combines human intelligence at scale with cutting-edge models to annotate all sorts of raw data, from text, to video, to images, to audio, to create the accurate ground truth needed for your models. Create and launch data annotation jobs easily through our plug and play graphical user interface, or programmatically through our API. -
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Kled
Kled
Kled is a secure, crypto-powered AI data marketplace that connects content rights holders with AI developers by providing high‑quality, ethically sourced datasets, spanning video, audio, music, text, transcripts, and behavioral data, for training generative AI models. It handles end-to-end licensing: it curates, labels, and rates datasets for accuracy and bias, manages contracts and payments securely, and offers custom dataset creation and discovery via a marketplace. Rights holders can upload original content, choose licensing terms, and earn KLED tokens, while developers gain access to premium data for responsible AI model training. Kled also supplies monitoring and recognition tools to ensure authorized usage and to detect misuse. Built for transparency and compliance, the system bridges IP owners and AI builders through a powerful yet user-friendly interface. -
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Shaip
Shaip
Shaip offers end-to-end generative AI services, specializing in high-quality data collection and annotation across multiple data types including text, audio, images, and video. The platform sources and curates diverse datasets from over 60 countries, supporting AI and machine learning projects globally. Shaip provides precise data labeling services with domain experts ensuring accuracy in tasks like image segmentation and object detection. It also focuses on healthcare data, delivering vast repositories of physician audio, electronic health records, and medical images for AI training. With multilingual audio datasets covering 60+ languages and dialects, Shaip enhances conversational AI development. The company ensures data privacy through de-identification services, protecting sensitive information while maintaining data utility. -
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Olmo 3
Ai2
Olmo 3 is a fully open model family spanning 7 billion and 32 billion parameter variants that delivers not only high-performing base, reasoning, instruction, and reinforcement-learning models, but also exposure of the entire model flow, including raw training data, intermediate checkpoints, training code, long-context support (65,536 token window), and provenance tooling. Starting with the Dolma 3 dataset (≈9 trillion tokens) and its disciplined mix of web text, scientific PDFs, code, and long-form documents, the pre-training, mid-training, and long-context phases shape the base models, which are then post-trained via supervised fine-tuning, direct preference optimisation, and RL with verifiable rewards to yield the Think and Instruct variants. The 32 B Think model is described as the strongest fully open reasoning model to date, competitively close to closed-weight peers in math, code, and complex reasoning.Starting Price: Free -
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DataHive AI
DataHive AI
DataHive provides high-quality, fully rights-owned datasets across text, image, video, and audio to power modern AI development. The platform sources, creates, and labels data through a global contributor network, ensuring accuracy, diversity, and commercial readiness. DataHive offers specialized datasets including e-commerce listings, customer reviews, multilingual speech, transcribed audio, global video collections, and original photo libraries. Each dataset is enriched with metadata such as pricing, sentiment, tags, engagement metrics, and contextual information. These resources support a wide range of use cases, from computer vision and ASR training to retail analytics, sentiment modeling, and entertainment AI research. Trusted by startups and Fortune 500 companies, DataHive is built to accelerate high-performance machine learning with reliable, scalable data. -
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TagX
TagX
TagX delivers comprehensive data and AI solutions, offering services like AI model development, generative AI, and a full data lifecycle including collection, curation, web scraping, and annotation across modalities (image, video, text, audio, 3D/LiDAR), as well as synthetic data generation and intelligent document processing. TagX's division specializes in building, fine‑tuning, deploying, and managing multimodal models (GANs, VAEs, transformers) for image, video, audio, and language tasks. It supports robust APIs for real‑time financial and employment intelligence. With GDPR, HIPAA compliance, and ISO 27001 certification, TagX serves industries from agriculture and autonomous driving to finance, logistics, healthcare, and security, delivering privacy‑aware, scalable, customizable AI datasets and models. Its end‑to‑end approach, from annotation guidelines and foundational model selection to deployment and monitoring, helps enterprises automate documentation. -
18
Keymakr
Keymakr
Keymakr provides image and video data annotation, along with data creation, collection, and validation services for AI and machine learning computer vision projects of any scale. The company’s core expertise lies in delivering high-quality training data for multimodal and embodied AI systems, and supporting human-verified annotation and LLM ground-truth validation of model outputs. Keymakr's motto, "Human teaching for machine learning," reflects its commitment to the human-in-the-loop approach. This is why the company maintains an in-house team of over 600 highly skilled annotators. Keymakr's goal is to deliver custom datasets that enhance the accuracy and efficiency of ML systems. To create precise datasets, Keymakr developed Keylabs.ai, a powerful enterprise-grade annotation platform that supports all annotation types. Keymakr also follows strict data security and compliance standards, holds ISO 9001 and ISO 27001 certifications, and maintains GDPR and HIPAA compliance.Starting Price: $7/hour -
19
GCX
Rightsify
GCX (Global Copyright Exchange) is a dataset licensing service for AI‑driven music, offering ethically sourced and copyright‑cleared premium datasets ideal for tasks like music generation, source separation, music recommendation, and MIR. Launched by Rightsify in 2023, it provides over 4.4 million hours of audio and 32 billion metadata-text pairs, totaling more than 3 petabytes, comprising MIDI, stems, and WAV files with rich descriptive metadata (key, tempo, instrumentation, chord progressions, etc.). Datasets can be licensed “as is” or customized by genre, culture, instruments, and more, with full commercial indemnification. GCX bridges creators, rights holders, and AI developers by streamlining licensing and ensuring legal compliance. It supports perpetual use, unlimited editing, and is recognized for excellence by Datarade. Use cases include generative AI, research, and multimedia production. -
20
Pixta AI
Pixta AI
Pixta AI is a cutting‑edge, fully managed data‑annotation and dataset marketplace designed to connect data providers with companies and researchers needing high‑quality training data for AI, ML, and computer vision projects. It offers extensive coverage across modalities, visual, audio, OCR, and conversation, and provides tailored datasets in categories like face recognition, vehicle detection, human emotion, landscape, healthcare, and more. Leveraging a massive 100 million+ compliant visual data library from Pixta Stock and a team of experienced annotators, Pixta AI delivers scalable, ground‑truth annotation services (bounding boxes, landmarks, segmentation, attribute classification, OCR, etc.) that are 3–4× faster thanks to semi‑automated tools. It's a secure, compliant marketplace that facilitates on‑demand sourcing, ordering of custom datasets, and global delivery via S3, email, or API in formats like JSON, XML, CSV, and TXT, covering over 249 countries. -
21
Scale Data Engine
Scale AI
Scale Data Engine helps ML teams build better datasets. Bring together your data, ground truth, and model predictions to effortlessly fix model failures and data quality issues. Optimize your labeling spend by identifying class imbalance, errors, and edge cases in your data with Scale Data Engine. Significantly improve model performance by uncovering and fixing model failures. Find and label high-value data by curating unlabeled data with active learning and edge case mining. Curate the best datasets by collaborating with ML engineers, labelers, and data ops on the same platform. Easily visualize and explore your data to quickly find edge cases that need labeling. Check how well your models are performing and always ship the best one. Easily view your data, metadata, and aggregate statistics with rich overlays, using our powerful UI. Scale Data Engine supports visualization of images, videos, and lidar scenes, overlaid with all associated labels, predictions, and metadata. -
22
StableVicuna
Stability AI
StableVicuna is the first large-scale open source chatbot trained via reinforced learning from human feedback (RHLF). StableVicuna is a further instruction fine tuned and RLHF trained version of Vicuna v0 13b, which is an instruction fine tuned LLaMA 13b model. In order to achieve StableVicuna’s strong performance, we utilize Vicuna as the base model and follow the typical three-stage RLHF pipeline outlined by Steinnon et al. and Ouyang et al. Concretely, we further train the base Vicuna model with supervised finetuning (SFT) using a mixture of three datasets: OpenAssistant Conversations Dataset (OASST1), a human-generated, human-annotated assistant-style conversation corpus comprising 161,443 messages distributed across 66,497 conversation trees, in 35 different languages; GPT4All Prompt Generations, a dataset of 437,605 prompts and responses generated by GPT-3.5 Turbo; And Alpaca, a dataset of 52,000 instructions and demonstrations generated by OpenAI's text-davinci-003.Starting Price: Free -
23
Defined.ai
Defined.ai
Defined.ai provides high-quality training data, tools, and models to AI professionals to power their AI projects. With resources in speech, NLP, translation, and computer vision, AI professionals can look to Defined.ai as a resource to get complex AI and machine learning projects to market quickly and efficiently. We host the leading AI marketplace, where data scientists, machine learning engineers, academics, and others can buy and sell off-the-shelf datasets, tools, and models. We also provide customizable workflows with tailor-made solutions to improve any AI project. Quality is at the core of everything we do, and we are in compliance with industry privacy standards and best practices. We also have a passion and mission to ensure that our data is ethically collected, transparently presented, and representative – since AI often reflects of our own human biases, it’s necessary to make efforts to prevent as much bias as possible, and our practices reflect that. -
24
Tülu 3
Ai2
Tülu 3 is an advanced instruction-following language model developed by the Allen Institute for AI (Ai2), designed to enhance capabilities in areas such as knowledge, reasoning, mathematics, coding, and safety. Built upon the Llama 3 Base, Tülu 3 employs a comprehensive four-stage post-training process: meticulous prompt curation and synthesis, supervised fine-tuning on a diverse set of prompts and completions, preference tuning using both off- and on-policy data, and a novel reinforcement learning approach to bolster specific skills with verifiable rewards. This open-source model distinguishes itself by providing full transparency, including access to training data, code, and evaluation tools, thereby closing the performance gap between open and proprietary fine-tuning methods. Evaluations indicate that Tülu 3 outperforms other open-weight models of similar size, such as Llama 3.1-Instruct and Qwen2.5-Instruct, across various benchmarks.Starting Price: Free -
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GigaChat 3 Ultra
Sberbank
GigaChat 3 Ultra is a 702-billion-parameter Mixture-of-Experts model built from scratch to deliver frontier-level reasoning, multilingual capability, and deep Russian-language fluency. It activates just 36 billion parameters per token, enabling massive scale with practical inference speeds. The model was trained on a 14-trillion-token corpus combining natural, multilingual, and high-quality synthetic data to strengthen reasoning, math, coding, and linguistic performance. Unlike modified foreign checkpoints, GigaChat 3 Ultra is entirely original—giving developers full control, modern alignment, and a dataset free of inherited limitations. Its architecture leverages MoE, MTP, and MLA to match open-source ecosystems and integrate easily with popular inference and fine-tuning tools. With leading results on Russian benchmarks and competitive performance on global tasks, GigaChat 3 Ultra represents one of the largest and most capable open-source LLMs in the world.Starting Price: Free -
26
Amazon Nova Forge
Amazon
Amazon Nova Forge is a groundbreaking service that enables organizations to build their own frontier models by leveraging early Nova checkpoints and proprietary data. It provides complete flexibility across the full training lifecycle, including pre-training, mid-training, supervised fine-tuning, and reinforcement learning. With access to Nova-curated datasets and responsible AI tooling, customers can create powerful and safer custom models tailored to their domain. Nova Forge allows teams to mix their own datasets at the peak learning stage to maximize accuracy while preventing catastrophic forgetting. Companies across industries—from Reddit to Sony—use Nova Forge to consolidate ML workflows, accelerate innovation, and outperform specialized models. Hosted securely on AWS, it offers the most cost-effective, streamlined path to building next-generation AI systems. -
27
Phi-4
Microsoft
Phi-4 is a 14B parameter state-of-the-art small language model (SLM) that excels at complex reasoning in areas such as math, in addition to conventional language processing. Phi-4 is the latest member of our Phi family of small language models and demonstrates what’s possible as we continue to probe the boundaries of SLMs. Phi-4 is currently available on Azure AI Foundry under a Microsoft Research License Agreement (MSRLA) and will be available on Hugging Face. Phi-4 outperforms comparable and larger models on math related reasoning due to advancements throughout the processes, including the use of high-quality synthetic datasets, curation of high-quality organic data, and post-training innovations. Phi-4 continues to push the frontier of size vs quality. -
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Human Native
Human Native
We’re bringing together rights holders and AI developers. Helping rights holders get compensation for copyrighted works. Enabling AI developers to responsibly acquire high-quality data. A comprehensive catalog of rights holders and their works. We help AI developers find the high-quality data they need. Rights holders have granular control over which individual works are open or closed to AI training. Monitoring solutions for detecting the misuse of copyrighted material. Enabling revenue for rights holders by licensing work for training with recurring subscriptions or revenue share. We help publishers get their content or data ready for AI models. We index, benchmark, and evaluate data sets to demonstrate their quality and value. Upload your catalog to the marketplace for free. Be compensated fairly for work. Opt-in and out of generative AI usages. Receive alerts for potential copyright infringement. -
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FinetuneDB
FinetuneDB
Capture production data, evaluate outputs collaboratively, and fine-tune your LLM's performance. Know exactly what goes on in production with an in-depth log overview. Collaborate with product managers, domain experts and engineers to build reliable model outputs. Track AI metrics such as speed, quality scores, and token usage. Copilot automates evaluations and model improvements for your use case. Create, manage, and optimize prompts to achieve precise and relevant interactions between users and AI models. Compare foundation models, and fine-tuned versions to improve prompt performance and save tokens. Collaborate with your team to build a proprietary fine-tuning dataset for your AI models. Build custom fine-tuning datasets to optimize model performance for specific use cases. -
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Hermes 3
Nous Research
Experiment, and push the boundaries of individual alignment, artificial consciousness, open-source software, and decentralization, in ways that monolithic companies and governments are too afraid to try. Hermes 3 contains advanced long-term context retention and multi-turn conversation capability, complex roleplaying and internal monologue abilities, and enhanced agentic function-calling. Our training data aggressively encourages the model to follow the system and instruction prompts exactly and in an adaptive manner. Hermes 3 was created by fine-tuning Llama 3.1 8B, 70B, and 405B, and training on a dataset of primarily synthetically generated responses. The model boasts comparable and superior performance to Llama 3.1 while unlocking deeper capabilities in reasoning and creativity. Hermes 3 is a series of instruct and tool-use models with strong reasoning and creative abilities.Starting Price: Free -
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Stable Beluga
Stability AI
Stability AI and its CarperAI lab proudly announce Stable Beluga 1 and its successor Stable Beluga 2 (formerly codenamed FreeWilly), two powerful new, open access, Large Language Models (LLMs). Both models demonstrate exceptional reasoning ability across varied benchmarks. Stable Beluga 1 leverages the original LLaMA 65B foundation model and was carefully fine-tuned with a new synthetically-generated dataset using Supervised Fine-Tune (SFT) in standard Alpaca format. Similarly, Stable Beluga 2 leverages the LLaMA 2 70B foundation model to achieve industry-leading performance.Starting Price: Free -
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GLM-5.1
Zhipu AI
GLM-5.1 is the latest iteration of Z.ai’s GLM series, designed as a frontier-level, agent-oriented AI model optimized for coding, reasoning, and long-horizon workflows. It builds on the GLM-5 architecture, which uses a Mixture-of-Experts (MoE) design to deliver high performance while keeping inference costs efficient, and is part of a broader push toward open-weight, developer-accessible models. A core focus of GLM-5.1 is enabling agentic behavior, meaning it can plan, execute, and iterate across multi-step tasks rather than simply responding to single prompts. It is specifically designed to handle complex workflows such as debugging code, navigating repositories, and executing chained operations with sustained context. Compared to earlier models, GLM-5.1 improves reliability in long interactions, maintaining coherence across extended sessions and reducing breakdowns in multi-step reasoning.Starting Price: Free -
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Datarade
Datarade
Skip months of research. Find, compare, and choose the right data for your business. Get free & unbiased advice by data experts. Get in-depth information about 2,000+ data providers curated across 210 data categories. Our experts advise and guide you through the whole sourcing process - free of charge. Find the right data that really fits with your goals, use cases, and key requirements. Briefly describe your goals, use cases, and data requirements. Receive a shortlist of suitable data providers by our experts. Compare data offerings and choose when you’re ready. We help you to identify the data providers that are really relevant to you, so you don’t waste time in unnecessary sales pitch calls. We connect you with the right point of contact, so you get a quick response. And last but not least, our platform and experts help you to keep track of your data sourcing process, so you get the best deal. -
34
Trinity-Large-Thinking
Arcee AI
Trinity Large Thinking is a frontier open source reasoning model developed by Arcee AI, designed specifically for complex, multi-step problem solving and autonomous agent workflows that require long-horizon planning and tool use. Built on a sparse Mixture-of-Experts architecture with roughly 400 billion total parameters but only about 13 billion active per token, the model achieves high efficiency while maintaining strong reasoning performance across tasks such as mathematical problem solving, code generation, and multi-step analysis. It introduces extended chain-of-thought reasoning capabilities, allowing the model to generate intermediate “thinking traces” before producing final answers, which improves accuracy and reliability in complex scenarios. Trinity Large Thinking supports a very large context window of up to 262K tokens, enabling it to process long documents, maintain state across extended interactions, and operate effectively in continuous agent loops.Starting Price: Free -
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Elemental Cognition
Elemental Cognition
Solve complex business problems when you can’t afford to be wrong. Use Elemental Cognition AI to deploy applications with transparent, provably correct reasoning. Large language models alone can’t be trusted to solve complex business problems. Deploy AI apps that explore and optimally solve complex problems when precision, accuracy, and transparency matter. Capture expert knowledge conversationally and turn it into a program automatically. Elemental Cognition compiles an easy-to-read English document into constraint-solving code so anyone can understand, test, and fine-tune the business logic governing your application. Manage the tradeoffs in hard problems and make sure your app never goes off the rails. Scale real-time constraint solving and optimization customized for your business using interactive AI that understands, reasons, and resolves complex tradeoffs to help users make the best decision. -
36
Lightning Rod
Lightning Rod
Lightning Rod is an AI platform designed to transform messy, unstructured real-world data into verified, production-ready training datasets and domain-specific AI models without requiring manual labeling. It enables users to generate high-quality, citable question–answer pairs from sources such as news articles, financial filings, and internal documents, turning raw historical data into structured datasets that can be used for supervised fine-tuning or reinforcement learning. It operates through an agent-driven workflow where users describe their goal, and the system automatically gathers sources, generates questions, resolves outcomes based on real-world events, and adds contextual grounding before training a model. A key innovation is its “future-as-label” methodology, which uses actual outcomes as training signals, allowing AI systems to learn directly from real-world results at scale instead of relying on synthetic or manually annotated data. -
37
MiniMax M2.5
MiniMax
MiniMax M2.5 is a frontier AI model engineered for real-world productivity across coding, agentic workflows, search, and office tasks. Extensively trained with reinforcement learning in hundreds of thousands of real-world environments, it achieves state-of-the-art performance in benchmarks such as SWE-Bench Verified and BrowseComp. The model demonstrates strong architectural thinking, decomposing complex problems before generating code across more than ten programming languages. M2.5 operates at high throughput speeds of up to 100 tokens per second, enabling faster completion of multi-step tasks. It is optimized for efficient reasoning, reducing token usage and execution time compared to previous versions. With dramatically lower pricing than competing frontier models, it delivers powerful performance at minimal cost. Integrated into MiniMax Agent, M2.5 supports professional-grade office workflows, financial modeling, and autonomous task execution.Starting Price: Free -
38
E5 Text Embeddings
Microsoft
E5 Text Embeddings, developed by Microsoft, are advanced models designed to convert textual data into meaningful vector representations, enhancing tasks like semantic search and information retrieval. These models are trained using weakly-supervised contrastive learning on a vast dataset of over one billion text pairs, enabling them to capture intricate semantic relationships across multiple languages. The E5 family includes models of varying sizes—small, base, and large—offering a balance between computational efficiency and embedding quality. Additionally, multilingual versions of these models have been fine-tuned to support diverse languages, ensuring broad applicability in global contexts. Comprehensive evaluations demonstrate that E5 models achieve performance on par with state-of-the-art, English-only models of similar sizes.Starting Price: Free -
39
GLM-5
Zhipu AI
GLM-5 is Z.ai’s latest large language model built for complex systems engineering and long-horizon agentic tasks. It scales significantly beyond GLM-4.5, increasing total parameters and training data while integrating DeepSeek Sparse Attention to reduce deployment costs without sacrificing long-context capacity. The model combines enhanced pre-training with a new asynchronous reinforcement learning infrastructure called slime, improving training efficiency and post-training refinement. GLM-5 achieves best-in-class performance among open-source models across reasoning, coding, and agent benchmarks, narrowing the gap with leading frontier models. It ranks highly on evaluations such as Vending Bench 2, demonstrating strong long-term planning and operational capabilities. The model is open-sourced under the MIT License.Starting Price: Free -
40
Sky-T1
NovaSky
Sky-T1-32B-Preview is an open source reasoning model developed by the NovaSky team at UC Berkeley's Sky Computing Lab. It matches the performance of proprietary models like o1-preview on reasoning and coding benchmarks, yet was trained for under $450, showcasing the feasibility of cost-effective, high-level reasoning capabilities. The model was fine-tuned from Qwen2.5-32B-Instruct using a curated dataset of 17,000 examples across diverse domains, including math and coding. The training was completed in 19 hours on eight H100 GPUs with DeepSpeed Zero-3 offloading. All aspects of the project, including data, code, and model weights, are fully open-source, empowering the academic and open-source communities to replicate and enhance the model's performance.Starting Price: Free -
41
DeepScaleR
Agentica Project
DeepScaleR is a 1.5-billion-parameter language model fine-tuned from DeepSeek-R1-Distilled-Qwen-1.5B using distributed reinforcement learning and a novel iterative context-lengthening strategy that gradually increases its context window from 8K to 24K tokens during training. It was trained on ~40,000 carefully curated mathematical problems drawn from competition-level datasets like AIME (1984–2023), AMC (pre-2023), Omni-MATH, and STILL. DeepScaleR achieves 43.1% accuracy on AIME 2024, a roughly 14.3 percentage point boost over the base model, and surpasses the performance of the proprietary O1-Preview model despite its much smaller size. It also posts strong results on a suite of math benchmarks (e.g., MATH-500, AMC 2023, Minerva Math, OlympiadBench), demonstrating that small, efficient models tuned with RL can match or exceed larger baselines on reasoning tasks.Starting Price: Free -
42
GPT-5.4 Pro
OpenAI
GPT-5.4 Pro is an advanced AI model developed by OpenAI to deliver high-performance capabilities for professional and complex tasks. It combines improvements in reasoning, coding, and agent-based workflows into a single unified system. The model is designed to work efficiently across professional tools such as spreadsheets, presentations, documents, and development environments. GPT-5.4 Pro also includes native computer-use capabilities, enabling AI agents to interact with software, websites, and operating systems to complete tasks. With support for up to one million tokens of context, it can manage long workflows and large datasets more effectively than previous models. The model also improves tool usage, allowing it to search for and select the right tools during multi-step processes. By delivering more accurate outputs with fewer tokens, GPT-5.4 Pro helps professionals complete complex work faster and more efficiently. -
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Hermes 4
Nous Research
Hermes 4 is the latest evolution in Nous Research’s line of neutrally aligned, steerable foundational models, featuring novel hybrid reasoners that can dynamically shift between expressive, creative responses and efficient, standard replies based on user prompts. The model is designed to respond to system and user instructions, rather than adhering to any corporate ethics framework, producing interactions that feel more humanistic, less lecturing or sycophantic, and encouraging roleplay and creativity. By incorporating a special tag in prompts, users can trigger deeper, internally token-intensive reasoning when tackling complex problems, while retaining prompt efficiency when such depth isn't required. Trained on a dataset 50 times larger than that of Hermes 3, much of which was synthetically generated using Atropos, Hermes 4 shows significant performance improvements.Starting Price: Free -
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WebAutomation
WebAutomation
Fast, Easy & Scalable Web Scraping. Scrape any website in minutes without coding using our ready made extractors or web based visual point and click tool. Get your Data in 3 easy steps. IDENTIFY. Enter URL, and Identify elements like text & images you would like to extract with our point and click feature. CREATE. Build and configure your extractor to get the data when and how you want it. EXPORT. Get structured data in your chosen format e.g JSON, CSV, XML. How can WebAutomation help your business? No matter your business type or sector, web scraping can help you understand your audience, generate leads or be more competitive with pricing. Online Finance & Investment Research Scrapers Finance & Investment Research. Enhance your financial models and track data to improve performance. Scrape and Aggregate data from… ONLINE. E-Commerce & Retail SCRAPER E-Commerce & Retail Monitor competitors, benchmark pricing, analyze customer reviews and gain competitor& market intelligence.Starting Price: $19 per month -
45
Reka Flash 3
Reka
Reka Flash 3 is a 21-billion-parameter multimodal AI model developed by Reka AI, designed to excel in general chat, coding, instruction following, and function calling. It processes and reasons with text, images, video, and audio inputs, offering a compact, general-purpose solution for various applications. Trained from scratch on diverse datasets, including publicly accessible and synthetic data, Reka Flash 3 underwent instruction tuning on curated, high-quality data to optimize performance. The final training stage involved reinforcement learning using REINFORCE Leave One-Out (RLOO) with both model-based and rule-based rewards, enhancing its reasoning capabilities. With a context length of 32,000 tokens, Reka Flash 3 performs competitively with proprietary models like OpenAI's o1-mini, making it suitable for low-latency or on-device deployments. The model's full precision requires 39GB (fp16), but it can be compressed to as small as 11GB using 4-bit quantization. -
46
doteval
doteval
doteval is an AI-assisted evaluation workspace that simplifies the creation of high-signal evaluations, alignment of LLM judges, and definition of rewards for reinforcement learning, all within a single platform. It offers a Cursor-like experience to edit evaluations-as-code against a YAML schema, enabling users to version evaluations across checkpoints, replace manual effort with AI-generated diffs, and compare evaluation runs on tight execution loops to align them with proprietary data. doteval supports the specification of fine-grained rubrics and aligned graders, facilitating rapid iteration and high-quality evaluation datasets. Users can confidently determine model upgrades or prompt improvements and export specifications for reinforcement learning training. It is designed to accelerate the evaluation and reward creation process by 10 to 100 times, making it a valuable tool for frontier AI teams benchmarking complex model tasks. -
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OpenAI o3-pro
OpenAI
OpenAI’s o3-pro is a high-performance reasoning model designed for tasks that require deep analysis and precision. It is available exclusively to ChatGPT Pro and Team subscribers, succeeding the earlier o1-pro model. The model excels in complex fields like mathematics, science, and coding by employing detailed step-by-step reasoning. It integrates advanced tools such as real-time web search, file analysis, Python execution, and visual input processing. While powerful, o3-pro has slower response times and lacks support for features like image generation and temporary chats. Despite these trade-offs, o3-pro demonstrates superior clarity, accuracy, and adherence to instructions compared to its predecessor.Starting Price: $20 per 1 million tokens -
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SAM 3D
Meta
SAM 3D is a pair of advanced foundation models designed to convert a single standard RGB image into a high-fidelity 3D reconstruction of either objects or human bodies. It comprises SAM 3D Objects, which recovers full 3D geometry, texture, and layout of objects within real-world scenes, handling clutter, occlusions, and diverse lighting, and SAM 3D Body, which produces animatable human mesh models with detailed pose and shape, built on the “Meta Momentum Human Rig” (MHR) format. It is engineered to generalize across in-the-wild images without further training or finetuning: you upload an image, prompt the model by selecting the object or person, and it outputs a downloadable asset ready for use in 3D applications. SAM 3D emphasizes open vocabulary reconstruction (any object category), multi-view consistency, occlusion reasoning, and a massive new dataset of over one million annotated real-world images, enabling its robustness.Starting Price: Free -
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Lux
OpenAGI Foundation
Lux is a powerful computer-use AI platform that enables agents to operate software just like a human user—clicking, typing, navigating, and completing tasks across any interface. It offers three execution modes—Tasker, Actor, and Thinker—giving developers the ability to choose between step-by-step precision, near-instant task execution, or long-form reasoning for complex workflows. Lux can autonomously perform actions such as crawling Amazon data, running automated QA tests, or extracting insights from Nasdaq’s insider activity pages. The platform makes it possible to prototype and deploy real computer-use agents in as little as 20 minutes using developer-friendly SDKs and templates. Its agents are built to understand vague goals, execute long-running operations, and interact naturally with human-facing software instead of relying solely on APIs. Lux represents a new paradigm where AI goes beyond reasoning and content generation to directly operate computers at scale.Starting Price: Free -
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Reka
Reka
Our enterprise-grade multimodal assistant carefully designed with privacy, security, and efficiency in mind. We train Yasa to read text, images, videos, and tabular data, with more modalities to come. Use it to generate ideas for creative tasks, get answers to basic questions, or derive insights from your internal data. Generate, train, compress, or deploy on-premise with a few simple commands. Use our proprietary algorithms to personalize our model to your data and use cases. We design proprietary algorithms involving retrieval, fine-tuning, self-supervised instruction tuning, and reinforcement learning to tune our model on your datasets.
