Predictive AI - Image and Video Enhancement and Analysis Platform
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Image and Video Enhancement and Analysis Platform. Suite of transformative based AI going beyond current market capabilities, allowing for advanced image and video enhancement and analysis. Already used in courts for defendant early release and prosecution.
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Interesting idea! And where else can this be applied besides courts?
Predictive AI
@mykyta_semenov_ Predictive AI can be used anywhere, with no limits on industry, purpose, or sector. Any place that depends on photos or videos can benefit from clearer visuals.
The idea is simple. Better clarity leads to better decisions, and Predictive AI gives you both. Have you tried it yet? Claim your code from here. We look forward to your feedback.
@pankajvnt No, I just watched the video. I don’t have a need for this, but I really liked the idea itself. I think your service could be interesting to large platforms that work with photos and videos, like Instagram. Have you thought about reaching out to them and selling your idea as a ready-made technology?
@aborschel @pankajvnt Really smooth UI for Predictive Equations fast, simple, and genuinely helpful for breaking down complex or unclear video evidence for court cases. The interface is clean, the explanations are clear, and it feels practical enough to use daily.
I suggest you add a few real-world example templates or a quick “starter guide” to help new users unlock its full value immediately. Also work on the marketing, so more people can find the project
Super interesting approach. Making messy visuals usable again feels incredibly valuable. Do you support batch processing?
@vik_sh
Absolutely — we support full batch processing.
On our platform, every image is processed as an individual job, and jobs are automatically grouped into a batch when you upload multiple files. That means you can drag-and-drop an entire folder or large set of images, and the system will handle them in parallel: each image gets its own job record (for tracking, credits, and telemetry), but they all run under the same batch so you can monitor the whole set together.
We also expose the same batching behavior through our API, so you can send multiple files programmatically and get structured job + batch IDs back for tracking or automation.
If you're processing high volumes or need workflow integration, happy to walk you through the API or set you up with a pilot.
@pankajvnt That’s a powerful use case, enhancement tools are common, but reliably doing it at a level trusted in legal settings is a completely different bar. The fact that it’s already being used in courts for both early release and prosecution says a lot about the tech’s rigor.
Curious how you handle chain-of-custody and auditability. Do you provide transparent logs or a forensic trail for how an image/video was enhanced so it can stand up under scrutiny?
@pankajvnt @fernando_scharnick Currently in the final output filename we include how it was enhanced, we are adding shortly additional similar authorship for external parties to source where the output came from (Predictive AI) but also what model was used. We hope once implemented that will become a standard for AI outputs.
@pankajvnt @aborschel That’s a great direction, having clear authorship + model attribution baked right into the output is exactly the kind of transparency standards the space needs. Once that lands, it’ll make audits and external verification so much smoother. Excited to see it become the norm!
Video enhancement for legal cases? That's powerful use case! ⚖️
What's the quality improvement you typically see? Can it work with really low-res footage?
@mskyow Hi there, the quality improvement can be anywhere from 20% to as much as 90% enhancement depending on type of noise or data loss. Some models perform better than others, some in combination with others to get even further.
Generally I would say you can expect to see anywhere from 33%+ depending on level of damage to the original media. Noise is entirely eliminated, most types of blur though this changes depending on the sensor.
It actually works better with low resolution! It can work on as much as 8k, but at that point you're really talking more about DPI than resolution, though both increase the perceptual quality of the output.
Hey, @aborschel. Just checked out Predictive AI, and this is genuinely impressive work. Video enhancement tools usually focus on surface-level fixes, but your approach of combining detail restoration, deblurring, denoising, recoloring, and harmonizing under one ecosystem feels far more aligned with real investigative workflows. The fact that your models are already being used in legal settings adds a whole different layer of seriousness to the platform.
The interface looks intuitive for non-technical users, but the underlying capability to upscale inputs from x2 to x8 puts your engine in a very different bracket.
I also like the clarity of the mission on your website. You are positioning machine vision not as an editing tool but as a way to help people perceive reality with sharper accuracy.
I am curious about one thing from a technical standpoint. When you process low-resolution or noisy footage, how are you balancing hallucination control with aggressive enhancement? Are you relying on a confidence mapping layer during reconstruction, or do you use a constraint-based approach to prevent over-generation in legal use cases?
Looking forward to learning more about your model architecture as you scale. Great launch today, and congratulations to the entire team.
@virajmahajan22 Love the insight! The models we use per their architecture do not introduce changes via content- it is possible because of how deblur works that removing the distortion can cause minor coloration changes on the green scale, but apart from this very mild effect there is no method to introduce hallucinations. What is possible with our Ai is they may fail to understand what they are improving, in which case you just don't get the output. A one in several million possibility.
Regarding reconstruction layers - we don't use any of what you mentioned, allowing our AI to remain lightweight. We use a chain of deterministic reconstruction layers that preserve pixel-level fidelity and suppress hallucination. There is no GAN architecture involved is another way to put it, so there is a near 0 chance of any additional details that aren't already present being introduced.
Hey Alexander @aborschel ,
Congrats on launching Predictive AI! It’s exciting to see how your platform is bringing cutting-edge technology into real-world applications like the legal field, especially with features like deblurring and denoising for video enhancement.
Just curious, how’s the response been so far? What kind of marketing goals or strategies are you focusing on to get the word out? Would love to hear more about your plans!
@mfarhan1107 The response has been largely positive- introducing new technologies for especially court use means we had to keep this absolutely grounded in truth and reality- basically, anything that could be enhanced, should independently enable information finding in the original media that would have been overlooked because of say noise or low light conditions.
So far the response is largely positive- there are those skeptical of the benefit, or concerned about possible missuses, but ah, this tech has already enabled prosecutions and defense, surgeries and satellite information data recovery. In every sense of the word we have kept the deployment as fair as possible to avoid bias introduction, and is part of why we are releasing more generalized versions of our models to the public- it is almost criminal given the benefit we have seen this technology enable (whether surgeries or enabling homicide investigations) to keep it from the general public when it can potentially offer similar benefits.
Predictive AI
Predictive Equations provides a simple promise. It brings clarity to situations where visuals were once uncertain. It helps teams find the truth inside messy or low quality data, and that is useful in every industry.
Predictive Equations focuses on one clear mission. It turns poor quality photos or videos into clean, usable, high fidelity visuals. Many organisations still depend on images to make important decisions, yet low resolution frames or noisy footage often hide key details. Predictive Equations solves this by restoring lost detail, cleaning blur and noise, correcting light, and improving colours. It can even upscale visuals up to eight times while keeping them natural.
This creates real impact. In legal and forensic work, a blurry camera frame that once showed almost nothing can become clear enough to identify a face or read a number plate. That level of clarity changes outcomes. It gives investigators better evidence and helps courts rely on information that is easier to verify. The company highlights cases where their technology supported early releases and acquittals, which shows that the product already delivers value in critical situations.
The strength of Predictive Equations is that it is not built only for one sector. Any industry that relies on images can use it. Hospitals and clinics can improve the quality of medical scans, which helps experts notice smaller details with more confidence. Manufacturing teams can strengthen visual inspections and improve quality control. Security teams can recover important details from low light footage. Even content creators, researchers, aviation teams, and space organisations benefit from having clearer and more accurate visuals.
The company also places strong attention on ethics, safety, and accessibility. Its goal is to support people who make decisions, not to replace them. It works to reduce bias in AI systems and follows responsible development practices.
Predictive AI
Frequently Asked Questions about Predictive AI
1. What is Predictive Equations?
Predictive Equations is an AI tool that cleans, restores, and enhances photos and videos. It turns low quality visuals into clearer and more detailed images that are easier to use in real work.
2. How does the technology improve low quality visuals?
It removes noise, sharpens details, fixes lighting issues, restores missing features, and upscales images while keeping them natural.
3. Who can use Predictive Equations?
Any industry that relies on images can use it. This includes legal teams, healthcare, manufacturing, security, engineering, research, and digital content production.
4. Is the enhancement process automatic?
Yes, the platform runs the enhancement automatically. Users upload the file, and the system processes it without any need for manual editing.
5. Can this tool be trusted for legal or forensic use?
Yes. Predictive Equations has already been used in real legal cases. It helps reveal important details in poor quality footage, which supports more accurate evaluations and outcomes.
6. Does the tool change the meaning of the original image?
The goal is to restore clarity, not to invent new elements. The system enhances what is already present and keeps the content authentic.
7. Is the platform secure?
The company places a strong focus on privacy and secure processing. Files are handled safely and are not exposed to third parties.
8. Can medical teams use this for scans?
Yes. The system can improve the clarity of certain medical images, which helps experts notice details that were hard to see before.
9. Does it work for videos?
Yes. Predictive Equations can enhance both individual frames and full video files, even in low light or noisy conditions.
10. How fast is the enhancement process?
Processing time depends on file size and complexity, but the platform is designed to deliver results quickly so teams can use the improved visuals without delay.