AI Model Generation Infrastructure

Generate specialized AI models instead of training them.

Pelora builds infrastructure that turns your data and task descriptions into specialized AI models - dramatically reducing the cost and time of model development.

The Problem

Custom AI models are still too expensive and slow to create.

Organizations increasingly need models adapted to their own data, domains, and workflows. But today, creating a specialized model is slow, expensive, and requires deep ML expertise - often across multiple costly iterations before anything useful is ready.

High Compute Cost

Fine-tuning and retraining require GPUs, infrastructure, and repeated experiments before a useful model is ready.

Slow Iteration

Every new task, customer, dataset, or domain requires another training cycle - slowing down product development and deployment.

Specialized Expertise

Building reliable custom models requires deep ML expertise, careful evaluation, and non-trivial engineering effort.

Technology

A new approach to model specialization.

Pelora replaces the conventional model development cycle with a new kind of infrastructure - one that understands tasks and data, and produces specialized models with a fraction of the usual effort.

Task & Data Understanding

The system reads your task description and examples to understand precisely what the target model needs to do.

Automated Model Creation

Pelora produces a specialized model directly - no manual training pipeline, no infrastructure to manage, no repeated experimentation.

Ready to Evaluate & Deploy

The resulting model can be tested on real data and deployed immediately - or iterated on rapidly if requirements change.

Use Cases

For teams that need many specialized models.

Research

Research Teams

Any team building AI on top of domain-specific data - whether in science, engineering, or industry - can get a specialized model without a full training infrastructure.

Enterprise

Enterprise AI

Create models specialized for internal documents, customer support, compliance, legal workflows, or proprietary knowledge.

AI Labs

AI Labs & Foundations

Accelerate experimentation and reduce the overhead of producing specialized models across many tasks and benchmarks.

Why Us

Built by AI researchers and ML systems builders.

Pelora is founded by Ben Shapira and Roi Cohen. Our work spans language models, model reliability, biomedical AI, adversarial robustness, and production ML systems. We combine frontier AI research with practical experience building and evaluating real-world AI systems.

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Publications
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Top-Tier Venues
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Industrial Research Labs
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Years Combined Experience

Selected Research

The Team

Meet the Founders

Ben Shapira, Co-Founder

Ben Shapira

Co-Founder · AI Researcher

M.Sc. in Computer Science from Tel Aviv University. Research Scientist at IBM Research working on biomedical and multimodal AI. Previously built production ML, NLP, and LLM systems at AlgoSec. Former intelligence analyst at IDF Unit 8200.

Roi Cohen, Co-Founder

Roi Cohen

Co-Founder · AI Researcher

PhD candidate in AI at HPI & TU Berlin, researching LLM reliability, factuality, and model behavior. Former IBM Research and Microsoft Research intern. Published at NeurIPS, EMNLP, TACL, and EACL. Former researcher at IDF Unit 8200.

Get in Touch

Building many specialized AI models?

We are speaking with AI teams, research labs, and companies that repeatedly train or customize models. If this sounds like you, we'd love to talk.

Contact Pelora