ABrush vs Halo by Scam AI: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of ABrush and Halo by Scam AI — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
ABrush
ABrush
AI image generation and editing studio that runs as a panel inside Adobe Photoshop, with 23+ models, ControlNet, LoRA styles and layer-native output.
Key features
- Photoshop-native panel: Generation, editing and upscaling happen on the open document and land on real layers, with no export-import round trip
- 23+ models in one panel: Switch between Stable Diffusion, Flux, Qwen Image and others per stage of a piece rather than committing to one provider
- Targeted editing: Inpaint or regenerate only the region that needs changing, keeping the rest of the composition untouched
- Pro conditioning controls: ControlNet support plus IP-Adapter and reference images for pose, composition and style control
- Custom LoRA styles: Load your own LoRA or style models to keep generations consistent with an established look
- Generation history: Every generation is saved and recoverable, so artists can return to an earlier variation without regenerating
- Shareable presets: Save prompts and settings as presets and share them across a team to reproduce a house style
- Commercial-safe data policy: Generated images belong to the user and customer images are not used for model training
Best for
- A concept artist generating multiple variations of a character directly in the working file and painting over the strongest one
- A retoucher fixing a single element of a composite with inpainting rather than regenerating the whole image
- A studio distributing a shared preset pack so several artists produce work in a consistent house style
- A freelance illustrator using a custom LoRA to keep generated assets on-style with a client's brand
- A designer upscaling and cleaning up a low-resolution asset without leaving Photoshop
- An agency handling commercial client work that needs assurance the images aren't used for model training
Halo by Scam AI
Reality Inc
AI trust platform that detects deepfakes, voice clones, and GenAI content across images, video, audio, IDs, and live video calls.
Key features
- Deepfake Detection: Catches face swaps, lip-sync, reenactment, and cloned voices that impersonate real people in image, video, and audio.
- GenAI Content Detection: Identifies fully synthetic images, video, and audio from Stable Diffusion, DALL·E, Midjourney, Sora, and ElevenLabs.
- Halo On-Device Call Protection: Runs 100% on-device to flag synthetic faces and face swaps live on Zoom, Teams, and Meet without recording or uploading anything.
- Eva-v1 Model Family: Eva-v1-Fast returns verdicts on images in under 2 seconds; Eva-v1-Pro delivers forensic-grade accuracy in under 4 seconds.
- Unified REST API: One integration handles both deepfake and GenAI detection across image, video, and audio via a single authenticated endpoint.
- Identity & Document Verification: Detects forged IDs, manipulated selfies, and AI-generated documents before onboarding completes.
- Add-on Defenses: Adaptive Defense, Active Liveness, and Express Lane low-latency mode extend detection with injection-attack protection and 3s response SLAs.
- Enterprise Compliance: GDPR compliant, SOC 2 Type II attested, and no media retention by default, with configurable retention for audit needs.
Best for
- KYC & Onboarding: Financial services and marketplaces block AI-generated selfies and forged IDs before an account is opened.
- Contact Center Fraud Prevention: Detect voice clones in real time to stop synthetic-caller attacks against call-center authentication.
- Executive Call Protection: Halo alerts staff to face-swap impersonations on video calls before authorizing wire transfers.
- Hiring & Remote Interviews: Recruiters catch deepfake candidates impersonating real engineers during video interviews.
- Content Moderation: Media platforms scan uploads at scale to flag GenAI images, video, and audio before they reach users.
- Insurance Claim Review: Detect manipulated photos and forged supporting documents submitted with claims.