10 Top Reinforcement Learning Companies and Startups to Watch in 2025

Reinforcement learning (RL) is evolving from research to real-world deployment. Reinforcement learning companies like Biomonadic, Surge AI, Predictiva, and Plaif are transforming how machines adapt, optimize, and make decisions across industries. These startups are embedding RL into domains such as gene therapy manufacturing, energy efficiency, and AI development workflows.

In this article, we highlight 10 pioneering reinforcement learning startups that are redefining AI adaptability and control in 2025. Selected for their technological innovation, application breadth, and commercial traction, these ventures showcase how RL is powering the next generation of intelligent systems, scaling across industries, and achieving high-ROI outcomes.

Global Startup Heat Map highlights Emerging Reinforcement Learning Startups to Watch

Through the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering over 7M+ startups, 20K+ technology trends plus 150M+ patents, news articles & market reports, we identified 10 reinforcement learning startups.

The Global Startup Heat Map below highlights the reinforcement learning startups you should watch in 2025, as well as the geo-distribution of 146 startups & scaleups we analyzed for this research.

According to our data, we observe high startup activity in the US and UK, followed by India. The top 5 startup hubs for reinforcement learning are San Francisco, London, Bangalore, New York City, and Hyderabad.

Explore Emerging Reinforcement Learning Startups to Watch in 2025

We hand-picked startups to showcase in this report by filtering for their technology, founding year, location, funding, and other metrics.

These reinforcement learning startups work on solutions ranging from cell and gene therapy and human feedback to autonomous AI trading platform and enterprise AI.

1. Biomonadic – AI-based Gene Therapy
2. Surge AI – Human-assisted Reinforcement Learning
3. Predictiva – Autonomous AI Trading Platform
4. Telemus AI – Artificial Intelligence as a Service
5. BUSINESS & AI – Enterprise AI Solutions
6. Adaptive ML – RL Production and Tuning
7. Plaif – Adaptive Learning Robots
8. Poolside – Coding Assistant
9. BeChained – AI-based Energy Management
10. MLGlow – AI-powered Cyber Defense Platform

1. Biomonadic

• Founding Year: 2023
• Location: Berkeley, CA, USA
• Use For: AI-based Gene Therapy

US-based startup Biomonadic develops an AI platform that optimizes cell and gene therapy manufacturing processes through reinforcement learning and large language models. The platform analyzes real-time bioprocessing data to dynamically adjust quality attributes and production yields.

Its adaptive control algorithms continuously refine protocols using time-series sensor inputs while its integrated LLM Copilot. This enables natural language queries for instant manufacturing insights.

Bionomadic applies transfer learning techniques across cell lines and implements customized protocols to address batch variability. This approach accelerates therapeutic development cycles, reduces production costs, and democratizes access to advanced cell and gene therapies.

2. Surge AI

• Founding Year: 2020
• Location: San Francisco, CA, USA
• Use For: Human-assisted Reinforcement Learning
• Funding: Surge AI has raised a total funding of USD 25 million

Surge AI is a US-based startup that operates a reinforcement learning with human feedback (RLHF) platform that combines human evaluators’ expertise with machine learning. It refines AI model outputs through real-time preference rankings and reward model training.

The platform also processes multilingual feedback from a global workforce to score responses based on accuracy, safety, and relevance. It then applies these metrics to fine-tune language models via API-integrated workflows. It distinguishes itself through SOC II-compliant security protocols, adaptive transfer learning across domains, and native SDK support integration into existing AI pipelines.

Surge AI maintains a network of specialists in multiple languages and implements hybrid human-AI annotation processes. This enables enterprises to develop aligned chatbots, content moderation systems, and generative tools while mitigating biases.

3. Predictiva

• Founding Year: 2020
• Location: Leicester, UK
• Use For: Autonomous AI Trading Platform

UK-based startup Predictiva develops autonomous AI trading platforms that leverage deep reinforcement learning algorithms to analyze real-time market data and execute trades across multiple asset classes. The startup also optimizes portfolio performance through continuous adaptation to evolving market conditions. The system processes streaming financial data using proprietary machine learning models trained on historical patterns and current market signals.

It also dynamically adjusts trading strategies while maintaining granular risk controls and compliance with financial regulations. Predictiva also combines neuro-symbolic AI architectures with institutional-grade security protocols. It eliminates emotional decision-making biases and implements safety mechanisms like automatic position closures during volatility spikes.

This technology enables hedge funds and asset managers to access predictive analytics capabilities previously limited to quantitative trading firms. The adaptive learning models improve strategy performance through each market cycle.

4. Telemus AI

• Founding Year: 2022
• Location: Australia
• Use For: Artificial Intelligence as a Service

Telemus AI offers artificial intelligence as a service (AIaaS) through a platform that integrates reinforcement learning algorithms and probabilistic models. The platform optimizes decision-making processes across finance, healthcare, and supply chain operations.

The system employs state agents trained to maximize reward functions by analyzing real-time data streams through API-connected enterprise systems. It dynamically adjusts strategies using Deep Q-Network architectures and hybrid human-AI validation workflows.

The platform combines cloud-based infrastructure with consulting services to embed pre-trained models into existing organizational frameworks. This expedited deployment of AI solutions does not require specialized in-house expertise or infrastructure overhauls. The platform also allows native interoperability with legacy software and adaptive transfer learning capabilities across industries.

Telemus AI enables enterprises and government entities to operationalize AI technologies that complement existing digital transformation strategies and democratize access to advanced machine learning tools.

5. BUSINESS & AI

• Founding Year: 2020
• Location: Tunisia
• Use For: Enterprise AI Solutions

BUSINESS & AI develops enterprise artificial intelligence solutions that integrate reinforcement learning frameworks to optimize complex decision-making processes across financial services and automotive industries. The platform processes multivariate business data through adaptive algorithms that dynamically balance multiple performance objectives.

It also analyzes real-time operational parameters against historical patterns to recommend risk-mitigation strategies and process improvements. Context ‘ AML, an AI-powered behavioral monitoring solution, detects money laundering risks by identifying anomalous transaction patterns. It uses unsupervised learning models that eliminate the dependency on predefined detection scenarios.

BUSINESS & AI combines deep reinforcement learning with business process mining so that the system autonomously refines detection thresholds while maintaining audit trails for regulatory compliance. This approach enables financial institutions to reduce false positives in anti-money laundering operations while adapting to emerging fraud patterns without manual rule updates.

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6. Adaptive ML

• Founding Year: 2023
• Location: France
• Use For: RL Production and Tuning
• Funding: Adaptive ML has raised a total funding of USD 20 million

Adaptive ML develops an AI optimization platform that applies reinforcement learning techniques to continuously refine large language models through production feedback and automated preference tuning. The platform processes real-time user interactions and synthetic data streams via its adaptive engine. It employs proximal policy optimization (PPO) algorithms to adjust model outputs while maintaining enterprise-grade security protocols within clients’ cloud environments.

The startup integrates a unified codebase called Harmony that combines reward modeling, inference acceleration, and reinforcement learning workflows. These automated testing cycles align LLM responses with specific business KPIs like customer retention or operational efficiency.

Adaptive ML abstracts complex RLHF/RLAIF pipelines into API-accessible services. The platform allows enterprises to implement state-of-the-art model adaptation without requiring machine learning expertise, deploying optimized versions of open-source models like Llama 3 through drop-in replacements for existing LLM infrastructure.

This approach reduces manual annotation costs through AI-generated feedback mechanisms while ensuring data sovereignty. Adaptive ML bridges the gap between academic reinforcement learning research and production systems for organizations to transform generic language models into domain-specific assistants.

7. Plaif

• Founding Year: 2020
• Location: South Korea
• Use For: Adaptive Learning Robots

Plaif develops adaptive learning robots that combine deep reinforcement learning and unsupervised learning algorithms through its PLAiF Adaptive Learning System (PALS). This enables autonomous problem-solving in industrial manufacturing environments.

The system processes multi-modal sensor data and real-time production feedback using neural networks trained on iterative trial-and-error cycles. These neural networks allow robots to master complex assembly tasks without predefined programming.

Plaif integrates 6D spatial recognition sensors and adaptive motion control architectures that dynamically adjust gripping forces and movement trajectories based on material properties and environmental changes. The startup addresses precision assembly challenges in electronics production lines through self-optimizing algorithms that reduce defect rates.

8. Poolside

• Founding Year: 2023
• Location: USA
• Use For: Coding Assistant
• Funding: Poolside raised USD 400 million at a USD 2 billion valuation.

Poolside develops AI-powered software engineering tools that leverage foundation models like Malibu, trained through reinforcement learning from code execution feedback. The platform analyzes codebases, generates context-aware suggestions, and automates repetitive programming tasks. The startup processes proprietary code repositories and documentation to fine-tune models on internal libraries and development patterns while maintaining strict data isolation within client-controlled infrastructure.

Poolside’s code completion engine, Point, delivers real-time suggestions through IDE plugins that incorporate project-specific context. The Poolside Assistant provides conversational coding support with smart context retrieval from connected development environments.

The system distinguishes itself through on-premises deployment capabilities for regulated industries, continuous model adaptation via execution feedback loops, and native integrations with version control systems that enable audit-compliant code generation.

9. BeChained

• Founding Year: 2020
• Location: USA
• Use For: AI-based Energy Management
• Funding: BeChained raised USD 8 million in a grant round.

BeChained develops an AI-based energy management platform that integrates reinforcement learning algorithms with industrial control systems to optimize energy consumption. The platform is useful in manufacturing processes to analyze real-time data from connected devices like pumps, compressors, and furnaces.

The system processes sensor inputs and production parameters through neural networks trained on operational patterns. Its dynamic adjusting of machine settings, such as motor speeds and valve positions, maintains output quality while reducing energy waste.

Bechained employs digital twin technology to simulate production environments and validate optimization strategies before implementation. This ensures compatibility with existing supervisory control and data acquisition (SCADA) and manufacturing execution system (MES) infrastructure through OPC standards.

The platform reduces energy costs while generating auditable carbon footprint reports for CO2 credit trading. The startup achieves it by continuously adapting to equipment performance degradation and market price fluctuations.

10. MLGlow

• Founding Year: 2022
• Location: Belgium
• Use For: AI-powered Cyber Defense Platform

MLGlow develops an RL-based digital twin platform that leverages reinforcement learning to simulate, optimize, and manage complex business processes in real-time. The startup’s technology creates dynamic virtual replicas of physical assets, processes, or systems, continuously learning from live operational data to improve decision-making and automate workflows.

By integrating advanced generative AI, large language models (LLMs), and edge AI, the platform enables adaptive modeling, predictive analytics, and rapid scenario testing across diverse industries.

MLGlow’s modular architecture supports integration with existing enterprise systems while ensuring scalability and data security. Through this approach, MLGlow empowers organizations to accelerate digital transformation and optimize resource allocation. It also drives operational efficiency by providing actionable insights and intelligent automation.

Discover All Emerging Reinforcement Learning Startups

The reinforcement learning startups showcased in this report are only a small sample of all startups we identified through our data-driven startup scouting approach. Download our free Industry Innovation Reports for a broad overview of the industry or get in touch for quick & exhaustive research on the latest technologies & emerging solutions that will impact your company in 2025!