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1,943 Listings in AI Agents Available
What is Carbon Robotics? Carbon Robotics builds AI-powered farm machines, led by the LaserWeeder G2, which uses lasers for weed control. Its Carbon AI Large Plant Model, trained on 150 million labeled plants across 15 countries and 100 crops, powers its machines. Key capabilities of Carbon Robotics LaserWeeder G2: laser-based weed control Carbon Autonomy: tractor autonomy for John Deere 6R, 8R, 8RX and 8RT (2019+) Carbon AI: Large Plant Model for plant identification Remote supervision: operator oversight with manual override Retrofit install: fits existing tractors without permanent modifications Cost reduction: up to 80% lower weeding cost versus traditional methods How Carbon Robotics works The Large Plant Model identifies crops and weeds, and the LaserWeeder G2 targets weeds with lasers instead of herbicide or hand labor. Carbon Autonomy installs on supported John Deere tractors, where remote operators supervise and can take manual control. Who uses Carbon Robotics? Carbon Robotics reports more than 200 growers in 15 countries. It cites yield increases of 5 to 50%, payback of 1 to 3 years and a machine lifespan of 7 to 10 years. Carbon Robotics pricing Carbon Robotics does not publish machine prices. The vendor cites a payback period of one to three years. Carbon Robotics alternatives Alternatives include Aerobotics for orchard insights, Taranis for field imagery analytics and Roboflow for building custom computer vision models.
Deployment
What is TypingMind? TypingMind is an LLM frontend chat UI that lets you use AI models through your own API keys. It is sold as a license rather than a subscription. Key capabilities of TypingMind Bring your own keys: Pay model providers directly AI agents: Custom agents Plugins: Extensions for chats Prompt library: Save prompts Document upload: Chat with files on higher tiers Multi-model chats: Compare GPT, Claude, Gemini and more on Premium How TypingMind works You enter API keys for providers like OpenAI or Anthropic and chat through TypingMind's interface, with data stored locally and usage billed by the provider. Who uses TypingMind? Individuals and teams wanting a better interface for LLM APIs. TypingMind pricing Third-party listings report Standard $39, Extended $79 and Premium $99 (list $198) as one-time purchases. API usage is paid separately to providers. TypingMind alternatives Alternatives include Open WebUI, LibreChat and AnythingLLM.
Deployment
What is Tethr? Tethr is a customer effort analytics AI agent offering AI that analyzes customer conversations to measure effort, predict outcomes and improve CX. Founded in 2016 and based in Austin, Texas, USA, Tethr helps contact centers and CX leaders automate customer effort analytics work and get results faster. Key capabilities of Tethr Customer effort scoring Predictive outcomes Agent behavior insights CX dashboards Automated call scoring Sentiment analysis How Tethr works Tethr takes audio and text as input and produces insights and scores. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Salesforce, HubSpot, Zoom and Genesys, so the agent works inside existing workflows. Who uses Tethr? Tethr is built for contact centers and CX leaders. It suits teams that want customer effort scoring and predictive outcomes without adding headcount, while keeping people in control of review and final decisions. Tethr vs CallMiner Tethr is often compared with CallMiner. Tethr stands out for customer effort scoring and agent behavior insights. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Amazon Rekognition? Amazon Rekognition is an AWS computer vision service that detects objects, faces and unsafe content in images and video. It is used through an API and billed on usage. Key capabilities of Amazon Rekognition Image analysis: Group 1 and Group 2 APIs for face and detection operations. Video analysis: Analyze streaming and stored video. Face liveness: Check that a live person is present, at $0.015 per check for the first 500K. Face metadata storage: Store face vectors and user vectors for search. Custom Labels: Train models to detect your own objects. Custom Moderation: Adapt content moderation, priced at $0.0012 per image for the first 1M. Image properties: Return attributes such as dominant colors, from $0.00075 per image. How Amazon Rekognition works You send an image or video to the Rekognition API, or train a Custom Labels model on your own data, and receive structured results such as labels, bounding boxes and confidence scores. Billing is per image processed or per video minute, and face features need stored vectors for later matching. Who uses Amazon Rekognition? Rekognition is used by developers and companies on AWS for identity verification, content moderation and media search. Applications decide how to act on the confidence scores that the API returns. Amazon Rekognition pricing Image analysis costs $0.001 per image for the first 1 million images per month, then $0.0008 for the next 4 million. Stored video label detection is $0.10 per minute and streaming events are $0.00817 per minute. New accounts get 1,000 images per month and 60 video minutes free for 12 months. Amazon Rekognition alternatives Alternatives include Google Cloud Vision AI, which offers image labeling and OCR, Microsoft Azure AI Vision, which adds spatial analysis and OCR, and Clarifai, which provides a full model platform.
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What is Parakeet Health? Parakeet Health is a healthcare-native AI platform that automates patient access workflows, inbound and outbound, across voice, SMS, fax and email. It was built by operators from One Medical, Epocrates, Stripe and Google for the complexity of practice management. Key capabilities of Parakeet Health Scheduling: Books, reschedules and cancels appointments Eligibility verification: Checks insurance eligibility and processes fax Referral management: Handles referrals and referral scheduling No-show recovery: Recovers no-shows and backfills cancellations Recall campaigns: Reactivates patients through outbound recall Patient FAQs: Answers questions on insurance, preparation, locations and policies 24/7 coverage: Operates around the clock, every day How Parakeet Health works Parakeet connects to a practice's EHR and existing VoIP or telephony systems, then handles patient calls, texts, faxes and emails for scheduling and access tasks. Implementation takes 4 to 6 weeks and the vendor says it needs under 6 hours of staff time. Who uses Parakeet Health? Medical practices and health systems that run busy call centers or lose revenue to no-shows. Vendor case studies cite a 38% rise in appointments, 42% more calls answered and a 60% cut in call center operating expense. Parakeet Health pricing Parakeet uses pay-for-performance pricing. It charges only for verified lift measured against your baseline, tied to appointments booked and revenue generated, with no software license or activity-based fees. Parakeet Health alternatives Alternatives include Notable for healthcare workflow automation, Regard for clinical AI, and Develop Health for patient access automation.
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What is Leaping AI? Leaping AI provides enterprise AI voice and text agents for customer service and appointment booking. The agents handle inbound calls, outbound campaigns and SMS conversations without requiring a separate phone system. Key capabilities of Leaping AI Inbound call answering: responds to every call within seconds Appointment booking: schedules and confirms appointments with callers Outbound campaigns: lead qualification calls at scale SMS follow-ups: text confirmations and reminders Call recording: recordings, transcripts and searchable logs Analytics: real-time dashboards and call summaries Human handoff: transfers to staff when needed How Leaping AI works Calls and texts are answered by a conversational agent that talks to the customer, books appointments and records outcomes. Calls are recorded and transcribed, with summaries and analytics available in a dashboard. Data syncs to HubSpot, Lead Perfection or custom tools so staff have context, and the agent can hand off to a human. Who uses Leaping AI? The vendor publishes case studies from Eurowings and Thompson Creek Window Company. It fits service businesses and enterprises with high call volume and appointment-driven sales or support. Leaping AI pricing Leaping AI does not publish prices. Its pricing page directs buyers to request a quote, and plans are scoped through a demo. Leaping AI alternatives Alternatives include Retell AI and Bland AI for voice agent platforms, Synthflow for no-code voice agents, and PolyAI for enterprise conversational voice.
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What is Audo AI? Audo AI is a set of audio and video processing tools for content creators and AI assistants. It offers a web-based Audo Studio and a REST API, with the stated goal of filtering a recording without adding synthetic content. Key capabilities of Audo AI Noise removal and voice enhancement: Cleans recordings without a studio setup Audio transcription: Supports 60 languages Script alignment: Matches audio to a provided script Silence removal and cutting: Trims dead air and cuts audio Loudness normalization: Targets levels for different publishing platforms Mixing and speaker leveling: Balances speakers and joins files Video audio tools: Extracts or swaps the audio track in video files MCP server access: Lets AI assistants such as ChatGPT and Claude call the tools How Audo AI works A user uploads a file in Audo Studio or sends it to the REST API, picks a tool, and receives the processed file. Audo says its processing filters the recording and adds nothing. File limits are 100 MB without an account and 10 GB with one, and uploaded files are deleted after 24 hours. The MCP server exposes the same tools to AI assistants and editors such as VS Code. Who uses Audo AI? Podcasters, video creators and developers who need quick audio cleanup use it, as do teams wiring audio processing into an app or AI assistant through the API or MCP server. Audo AI pricing Audo uses a credit system where different tools cost 1 to 3 credits per minute of audio. A free trial covers the first minutes of any file with limited daily uses and no account required. Per-credit dollar prices are not stated on the page reviewed. Audo AI alternatives Alternatives include Adobe Podcast Enhance Speech for voice cleanup, Descript for transcript-based editing, and Auphonic for automatic leveling and loudness normalization.
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What is Botter? Botter is an enterprise conversational AI platform specializing in Arabic-language chatbots and voicebots for business automation. Key capabilities of Botter Arabic NLU: Understands multiple Arabic dialects and 20+ languages. Voice bot: Arabic speech recognition and text-to-speech. Cognitive services: Computer vision, OCR, sentiment analysis and face recognition. WhatsApp campaigns: Campaign manager for WhatsApp marketing. Omnichannel deployment: Messenger, Instagram, Teams, web, mobile apps and IVR. How Botter works Teams build chatbots and voicebots on the platform and deploy them across channels including WhatsApp, Facebook Messenger, Instagram, Twitter DMs, Microsoft Teams, Skype, websites, mobile apps and IVR. Voice bots use Arabic speech recognition and synthesis, and cognitive services add vision and sentiment features. Contact center connections include Genesys and Cisco. Who uses Botter? Banks, healthcare providers, insurers, retailers, airlines and government bodies in Arabic-speaking markets. Named customers include Bank Al-Jazira, SABIC, Modon and Bupa. Botter pricing No pricing or free trial is disclosed on the homepage. Buyers contact the sales team for a quote. Botter alternatives WideBot is another Arabic conversational AI vendor, Jelou targets Latin American messaging automation, and Botpress and Voiceflow are general-purpose bot builders.
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What is Google Cloud Vision AI? Google Cloud Vision AI is an image understanding AI agent offering Google Cloud vision APIs for image labeling, OCR, face and landmark detection. Founded in 2016 and based in Mountain View, California, USA, Google Cloud Vision AI helps developers on Google Cloud automate image understanding work and get results faster. Key capabilities of Google Cloud Vision AI Image labeling OCR Safe search moderation Vertex AI vision models Custom model training Edge and cloud deployment How Google Cloud Vision AI works Google Cloud Vision AI takes image and video as input and produces structured data and text. It is powered by Google (in-house models) models, with the vendor managing prompts, models and updates. It connects to tools such as AWS, Azure, Google Cloud and NVIDIA, so the agent works inside existing workflows. Who uses Google Cloud Vision AI? Google Cloud Vision AI is built for developers on Google Cloud. It suits teams that want image labeling and OCR without adding headcount, while keeping people in control of review and final decisions. Google Cloud Vision AI vs Amazon Rekognition Google Cloud Vision AI is often compared with Amazon Rekognition. Google Cloud Vision AI stands out for image labeling and safe search moderation. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is IMATAG? IMATAG is a digital watermarking and visual content protection company based in France. It embeds invisible identifiers in images and video and pairs them with visual recognition to track unauthorized use online. Key capabilities of IMATAG Leaks: Embeds invisible identifiers before sharing to trace the source of leaked assets. Monitor: Tracks unauthorized use of images and video online. Authenticity: Proves provenance and genuineness through watermarking. Visual recognition: Reverse image search that matches cropped, resized or compressed copies. Custom search: Databases built from proprietary crawlers and partner sources. Earned media tracking: Calculates reach of brand content. How IMATAG works IMATAG adds a hidden watermark to a visual asset before distribution. Its crawlers and visual recognition then search the web for copies, even when cropped, resized, compressed or distorted, and a watermark read identifies the leaked copy or confirms authenticity. The vendor is a member of C2PA and the Content Authenticity Initiative. Who uses IMATAG? Entertainment, real estate, media and publishing, brands and agencies. Use cases listed by the vendor include copyright protection, leak prevention, asset tracking, brand protection and anti-piracy. IMATAG pricing IMATAG does not publish prices. Pricing is available on request, and a demo can be scheduled through the vendor. IMATAG alternatives Steg.AI also does watermarking, while Landing AI, Clarifai and Viso Suite are general computer vision platforms. IMATAG specializes in content tracing.
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What is NVIDIA NeMo? NVIDIA NeMo is a generative AI framework AI agent offering NVIDIA framework and microservices for building, customizing and deploying generative AI models. Founded in 2019 and based in Santa Clara, California, USA, NVIDIA NeMo helps enterprise AI developers automate generative AI framework work and get results faster. Key capabilities of NVIDIA NeMo LLM training and customization Guardrails Speech AI NeMo microservices Open-source community Distributed training How NVIDIA NeMo works NVIDIA NeMo takes text, audio and code as input and produces models and APIs. It is powered by NVIDIA Nemotron and open models models, with the vendor managing prompts, models and updates. It connects to tools such as Python, CUDA, Hugging Face and Kubernetes, so the agent works inside existing workflows. Who uses NVIDIA NeMo? NVIDIA NeMo is built for enterprise AI developers. It suits teams that want LLM training and customization and guardrails without adding headcount, while keeping people in control of review and final decisions. NVIDIA NeMo vs Hugging Face NVIDIA NeMo is often compared with Hugging Face. NVIDIA NeMo stands out for LLM training and customization and speech AI. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Flagright? Flagright is an AI-native operating system for financial crime compliance. It combines transaction monitoring, case management, dynamic risk scoring, watchlist screening and regulatory filing. Key capabilities of Flagright AI Forensics: Explainable agents that automate investigations. Transaction monitoring: Real-time detection with millisecond rules. Dynamic risk scoring: Reassesses risk as behavior changes. Case management: Audit trails and workflows. Watchlist screening: Sanctions and PEP databases. Regulatory filing: SAR and STR filing to FinCEN and 70+ jurisdictions. No-code rules: Rules built in about 3 minutes on average. How Flagright works Transactions stream into the platform, rules and risk scores flag alerts, and AI Forensics agents investigate with explainable reasoning. Analysts review in case management and file reports. The vendor reports 93% fewer false positives and 50% faster investigations. Who uses Flagright? Payment processors, digital banks, neobanks, banks, credit unions, brokerages, crypto platforms and remittance providers. Flagright pricing Flagright does not publish pricing on its homepage. Flagright alternatives Sedric and Saifr are compliance AI tools, Inscribe focuses on document fraud detection, and HighRadius is accounts receivable software. Flagright centers on AML and transaction monitoring.
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