# Datature vs FieldDay · Real-World AI

Datature records 24,530 monthly visits with -23.2% month-over-month growth and Freemium, Paid, Contact for Pricing pricing. FieldDay · Real-World AI records 0 monthly visits with — growth and Freemium pricing.

| Metric | [Datature](https://openaitools.app/tool/datature) | [FieldDay · Real-World AI](https://openaitools.app/tool/fieldday) |
| :--- | :--- | :--- |
| Website URL | https://datature.io | https://apps.apple.com/us/app/fieldday-real-world-ai/id6448133483 |
| Categories | AI Developer Tools, AI Image Recognition, AI App Builder, No-Code&Low-Code | AI App Builder, No-Code&Low-Code, AI Image Recognition, AI Models |
| Pricing Model | Freemium, Paid, Contact for Pricing | Freemium |
| Monthly Visits | 24,530 | 0 |
| MoM Growth Rate | -23.2% | — |
| Primary Market | India | Global |
| Direct Visits | 9,829 | 0 |
| Review Score | 4.2 | 4.2 |
| Saved Count | 0 | 2 |
| Supported Platforms | Website | App |

## Datature

Datature is a computer vision platform built for teams that need to move from raw imagery to working vision models without assembling a patchwork of tools. It bundles dataset management, annotation, training, evaluation and deployment into one workspace, so engineers, data labelers and domain experts can collaborate on the same project instead of passing files between disconnected systems.

The labeling side leans heavily on AI assistance: auto-annotation, model-assisted labeling, consensus and approval workflows, and support for bounding boxes, segmentation, keypoints and 3D annotation. From there, users train classification, object detection, keypoint and segmentation models through a drag-and-drop workflow with tunable architecture, batch size and epoch settings, then review performance visually against ground truth.

Deployment is treated as a first-class step rather than an afterthought. Models can be pushed to edge devices or cloud environments through hosted APIs, with monitoring, data locality options and compliance support for regulated industries such as healthcare, energy, agriculture, manufacturing, retail and smart city projects. A free tier exists for hobbyists, while teams scale into paid tiers and enterprise agreements.

**Pricing & Plans:** Freemium with paid tiers. The Free plan supports up to 300 images, 300MB storage, 5 exportable models and 300 monthly training minutes. Developer, Professional and Enterprise plans are quoted on request and add larger datasets, deployment containers, regional servers and compliance features. Add-ons include extra training minutes, seats and deployment containers.

- **AI-assisted annotation:** Speed up data prep with auto-annotation, model-assisted labeling, pixel-precise segmentation tools and consensus/approval workflows for consistent quality across annotators.
- **No-code model training:** Build training workflows in a drag-and-drop interface, tune architecture, batch size and epochs, and visually evaluate model performance against ground truth.
- **Multi-task vision models:** Train classification, object detection, keypoint and segmentation models to cover tagging, tracking, pose estimation and pixel-level analysis use cases.
- **Flexible deployment:** Ship models to edge or cloud environments via hosted APIs, with monitoring, scaling and secure authentication for production inference.
- **Enterprise governance:** Region-specific servers, workspace access controls, and HIPAA and SOC 2 compliance support for regulated and government workloads.

**Strengths:** Covers annotation, training and deployment in one platform so teams avoid juggling separate vendors; Genuinely usable without deep ML expertise thanks to the visual training workflow; Strong compliance and data-locality story for healthcare, government and regulated industries; Free tier is workable for small proofs of concept and academic projects

**Limitations:** Paid tiers are quote-based, so pricing is not transparent before a sales conversation; Free plan caps at 300 images and 300 training minutes, which is quickly outgrown; Advanced governance features such as ontology controls and region-specific servers stay behind higher tiers

[Profile (Markdown)](https://openaitools.app/tool/datature.md)

## FieldDay · Real-World AI

FieldDay turns the iPhone into a self-contained applied-ML environment. Instead of sending photos to a cloud service or hiring a data scientist, you define categories for the objects, gestures, or scenes you want the camera to recognize, then record samples from different angles and lighting conditions. FieldDay trains a compact classifier on-device, lets you test it live in the camera view, and gives you a simple correction loop: every time the model misreads something, you mark the right answer and it learns from that example. The whole loop is designed to take minutes rather than weeks, and everything happens in a friendly, visual interface that requires no programming.

Once a model behaves the way you want, FieldDay offers two paths forward. You can keep it in the app and attach an action: connect HomeKit devices or scenes to specific categories so that simply pointing the camera at a room, lamp, fan, or outlet surfaces the right smart-home controls. Or you can export the model to platforms you already use, including Siri Shortcuts for image-based predictions, Snap Lens Studio, and Xcode for deeper integration into your own projects and workflows.

The app is aimed at a broad audience — hobbyists experimenting with computer vision, makers building camera-driven gadgets, teachers creating interactive lessons, and product teams prototyping retail or accessibility experiences. FieldDay was developed by New Material, Inc. (with ties to New Material Studio Ltd in the UK) and is published on the Apple App Store for iPhone running iOS 16 or later. It is a genuine first-party app, not an unofficial or third-party clone of a larger brand.

**Pricing & Plans:** Free to download and — per the latest App Store update — free to use: version 1.2.0 removed subscriptions and in-app purchases so all features are available at no cost. Earlier releases experimented with a FieldDay Pro subscription and paid training credits, so ignore old pricing references you may find online.

- **On-device model training:** Collect a custom image dataset with your iPhone camera and train a vision classifier right on the phone, with no cloud round-trip and no code.
- **Correction-based fine-tuning:** Every misclassification can be corrected in place, letting the model improve iteratively as you keep using it in the real world.
- **HomeKit actions:** Assign HomeKit lights, outlets, fans, or scenes to specific categories so that recognizing an object in the camera view instantly brings up the matching controls.
- **Model export:** Take your trained classifier beyond FieldDay and reuse it in Siri Shortcuts, Snap Lens Studio, Xcode, and other popular formats and tools.
- **Real-time camera testing:** Test predictions live through the camera while you are still training, so you can see exactly when a model is good enough to ship.

**Strengths:** Genuinely no-code: the entire pipeline from data collection to a working classifier happens in one visual iPhone app.; Fast iteration loop — collection, training, live testing, and correction are all in the same place, so experiments take minutes.; Useful escape hatches: HomeKit actions and export options (Shortcuts, Lens Studio, Xcode) keep models from being locked inside the app.; Now completely free after the 1.2.0 update removed subscriptions and in-app purchases.

**Limitations:** iPhone-only (iOS 16+) — there is no Android or web version.; Requires an Apple device for the smart-home and Shortcuts integrations to be useful at all.; Accuracy depends heavily on the quality and variety of the training data you collect yourself.

[Profile (Markdown)](https://openaitools.app/tool/fieldday.md)

## Frequently Asked Questions

### How do Datature and FieldDay · Real-World AI compare in monthly traffic?

Datature has 24,530 monthly visits, while FieldDay · Real-World AI has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Datature has a month-over-month growth rate of -23.2%; FieldDay · Real-World AI has —.

### How does pricing compare?

Datature: Freemium, Paid, Contact for Pricing. Freemium with paid tiers. The Free plan supports up to 300 images, 300MB storage, 5 exportable models and 300 monthly training minutes. Developer, Professional and Enterprise plans are quoted on request and add larger datasets, deployment containers, regional servers and compliance features. Add-ons include extra training minutes, seats and deployment containers. FieldDay · Real-World AI: Freemium. Free to download and — per the latest App Store update — free to use: version 1.2.0 removed subscriptions and in-app purchases so all features are available at no cost. Earlier releases experimented with a FieldDay Pro subscription and paid training credits, so ignore old pricing references you may find online.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Base44](https://openaitools.app/tool/base44) | 14,039,232 | +0.5% | Freemium, Paid, Contact for Pricing | Build working apps, websites, and AI agents by describing them | [.md](https://openaitools.app/tool/base44.md) |
| 2 | [RunningHub](https://openaitools.app/tool/runninghub) | 3,105,554 | -28.5% | Freemium | Cloud ComfyUI platform to run workflows and build AI apps | [.md](https://openaitools.app/tool/runninghub.md) |
| 3 | [Ultralytics](https://openaitools.app/tool/ultralytics) | 793,423 | +8.7% | Freemium | Real-time vision AI models and a full platform to train, annotate, and deploy them | [.md](https://openaitools.app/tool/ultralytics.md) |
| 4 | [Pl@ntNet](https://openaitools.app/tool/plantnet-org) | 439,904 | +34.9% | Free | Identify plants from photos and contribute to biodiversity science | [.md](https://openaitools.app/tool/plantnet-org.md) |
| 5 | [SuperAnnotate](https://openaitools.app/tool/super-annotate) | 386,034 | +37.4% | Free Trial, Contact for Pricing | AI data infrastructure for building production-grade models | [.md](https://openaitools.app/tool/super-annotate.md) |
| 6 | [Adalo](https://openaitools.app/tool/adalo) | 379,914 | +7.5% | Freemium | AI no-code builder that turns one sentence into native iOS, Android, and web apps | [.md](https://openaitools.app/tool/adalo.md) |
| 7 | [Encord](https://openaitools.app/tool/encord-com) | 244,204 | +9.4% | Contact for Pricing | The multimodal data layer for computer vision and physical AI teams | [.md](https://openaitools.app/tool/encord-com.md) |
| 8 | [Defined.ai](https://openaitools.app/tool/definedcrowd-com) | 146,251 | -21% | Contact for Pricing | Enterprise AI training data, annotation and evaluation services | [.md](https://openaitools.app/tool/definedcrowd-com.md) |
| 9 | [Voxel51](https://openaitools.app/tool/voxel51-com) | 117,715 | -8.2% | Contact for Pricing | Find where your physical AI models fail, then fix the data. | [.md](https://openaitools.app/tool/voxel51-com.md) |
| 10 | [Memento Database](https://openaitools.app/tool/memento-database) | 69,682 | +53.9% | Freemium | A no-code, cross-platform database you can shape into any app | [.md](https://openaitools.app/tool/memento-database.md) |

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Source: https://openaitools.app/compare/datature-vs-fieldday

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