We Build Advanced AI and Reinforcement Learning Solutions to Solve Your Most Complex Business Problems
INM Consulting provides the elite, specialist expertise you need for a critical project—without the cost and complexity of hiring a full-time, in-house team.
About Us
At INM Consulting, we specialize in delivering cutting-edge data science and machine learning solutions tailored to your business needs. With extensive experience across various industries, we help organizations leverage data to drive innovation and achieve their strategic goals.
Our Specialist Capabilities
Agentic AI for Risk & Automation
We design and deploy autonomous AI agents that can reason, plan, and execute complex tasks. We turn your public and private data into an active tool for quantifying risk, automating research, and driving decisions.
Learn More →Reinforcement Learning for Process Optimisation
Go beyond predictive analytics. We build digital twins of your operations and deploy RL controllers that learn to actively optimize your processes, minimizing waste, reducing costs, and improving throughput.
Learn More →Custom LLM & NLP for R&D
Generic LLMs can't understand your domain. We fine-tune and deploy custom NLP models on your proprietary data, unlocking insights from millions of biomedical or technical documents.
Learn More →Our Approach
- Initial Consultation and Stakeholder Engagement:We begin by engaging with stakeholders to understand their business objectives and challenges. This involves detailed discussions to gather requirements, define success metrics, and align on project goals. This stage is crucial for setting a clear direction and ensuring that all parties have a shared vision.
- Data Collection and Exploration:Once the objectives are clear, we move on to data collection. This involves identifying relevant data sources, ensuring data quality, and performing exploratory data analysis (EDA). EDA helps us understand the data's structure, detect patterns, and identify potential issues such as missing values or outliers.
- Feasibility Testing and Prototyping:We conduct feasibility tests to validate the project's potential. This includes back-of-the-envelope calculations and developing quick prototypes to test hypotheses. The goal is to identify any major roadblocks early and ensure that the project is viable before investing significant resources.
- Model Development and Iteration:In this stage, we develop machine learning models tailored to the project's needs. We use an iterative approach, continuously refining models based on feedback and performance metrics. This involves selecting appropriate algorithms, tuning hyperparameters, and validating models using cross-validation techniques.
- Deployment and Integration:Once the models are validated, we deploy them into the production environment. This involves integrating the models with existing systems and ensuring they operate efficiently at scale. We also set up monitoring systems to track model performance and make adjustments as needed.
- Continuous Feedback and Improvement:Post-deployment, we maintain an open line of communication with stakeholders to gather feedback and make iterative improvements. This ensures that the solution continues to meet business needs and adapts to any changes in the environment or objectives.
- Documentation and Knowledge Transfer:Finally, we document the entire process, including data sources, model specifications, and deployment details. We conduct knowledge transfer sessions to empower stakeholders and ensure they can maintain and extend the solution independently.
Our Work: From Manufacturing Optimization to Pharmaceutical R&D
Manufacturing - RL Production Controller
Developed and deployed a Reinforcement Learning controller to minimize losses in production line, using digital twin simulation and real-time control of process variables.
Reinforcement Learning • Manufacturing
Pharmaceuticals - Genetic Data & NLP
Built ML workflow for 500K patient genetic data analysis and NLP models for 20M biomedical articles, delivering dashboards and APIs.
NLP & ML • Pharmaceuticals
Agriculture - Carbon & Deforestation ML
Developed ML models for agriculture carbon emissions reduction and deforestation risk prediction, including microbial data analysis and satellite imagery processing.
ML & NLP • EnvironmentTrusted by Industry Leaders
Our Clients
Ready to Transform Your Data?
Let's discuss how we can help you achieve your business goals with data-driven solutions.
Get In Touch