TheAppliedAILab
ThatShips.
We take the AI problems your team can't solve with existing methods and work them through to production. Every engagement produces a deployed system, filed patents, and research papers submitted to venues like NeurIPS and ICML. Not a deck about what might be possible.
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Fourpillars.Onepartner.
Applied AI R&D
We embed with your research and engineering teams to work on problems that don't have known answers yet. Novel architectures, domain-specific models, training methodologies that don't exist in the literature. We run the experiments, validate the results, and hand you a system that works. Not a report about what might work.
Product Development
A paper without a product is a citation. We build the systems that put research findings in front of users. Inference pipelines, APIs, deployment infrastructure. The model works in a notebook. We make it run in production.
Patent Strategy & Filing
Most AI companies generate patentable IP without realizing it. We surface what's novel in your model design, training process, and application layer, then file before someone else does. Patents filed across US, EU, and international jurisdictions.
Research Publications
We publish at venues that matter. Peer-reviewed papers that build your institution's scientific credibility and attract the kind of talent that reads papers before job listings.
How We Work
Most consultants advise. We build, file, and publish.
The gap between AI research and production is where most engagements stall. We run research and engineering in parallel so the system you ship is the system the science describes.
Discover & Define
We scope the problem with your domain experts and research leads before writing a line of code. The goal is to find the real constraint, not the assumed one. Most projects change direction in this phase. That's the point.
Discovery artifacts
Root problem
Stated vs. actual
Key constraint
Time / budget / data
Success criteria
How we know it worked
Team map
Domain experts involved
Data inventory
Available signals
Assumptions
To test in week one
Scienceisourproduct.
The papers go to peer review. The architecture stays proprietary. We run IP filings in parallel with every research engagement so nothing goes public before it's protected.
Trustedbyteamsthatbuildseriously.
Ethan and his team helped us execute the whole SMP platform, from planning to MVP they were ensuring timely delivery. I strongly recommend Evlogia if you are planning your startup and need a technology partner.
”Founder, SellMyPlot
Who We Are
Whoweare.
Evlogia is an applied AI research lab. We solve AI problems that don't have published solutions yet, build the systems that act on what we find, and file the patents before the research goes public.
We do the work.
We don't advise on AI strategy and leave you to figure out the execution. We write the code, run the experiments, build the systems, and stand behind the results.
We protect what we build.
Every engagement includes an IP review. If the work produces something novel, it gets filed. Most firms treat patents as an afterthought. We treat them as a deliverable.
We publish what we find.
If the science is good enough, it goes to peer review. This isn't a marketing exercise. Published research attracts better talent, builds institutional credibility, and forces rigor on every project.
Questionswegetasked.
Let's talk about
your problem.
Bring us your hardest AI problem. Thirty minutes. No pitch. Just a focused conversation about whether we're the right fit.
Let'ssolvesomethingworthpublishing.
Bring us your hardest AI problem. We'll scope it, build it, protect it, and if the science holds up, publish it. Thirty minutes. No pitch. Just a focused conversation about whether we're the right fit.