Our revolutionary CML+ platform uses the power of LLMs to deploy a Causal AI application for outcome improvement for your organization tailored to your data and KPIs in record time.
The end product is a hybrid SaaS-LLM application that combines the best of both worlds
Conduct your business tasks and take steps to improve organizational outcomes based on Causal AI through intuitive dashboards and actionable interfaces designed for your workflows.
A conversation window powered by LLMs to have a dialogue with an AI agent about your data, ML insights, and evidence-based actions you can take to improve outcomes.
Our proven pipeline transforms your data into a production Causal AI application
We analyze your data using LLM-powered AI agents and set up a data lake that functions as a Single Source of Truth (SST) for the application. Our agents are designed to identify key components of data based on the value of data necessary to develop a Causal AI application to improve organizational outcomes. Our AI Engineers and Data Engineers supervise this process.
Using our CML Insight Causal Insights software, we analyze the data in the SST to uncover causal relationships in your data. Where available, we also evaluate the efficacy of past interventions you have executed on KPIs that matter to your business. All these findings are made available to the application being built and to LLM RAG with vector embeddings to equip agents with causal reasoning capabilities.
Using our CML Insight Curator software, we extract high-quality, peer-reviewed research findings on outcome improvement for your domain. We merge these findings with any organizational findings you have to further strengthen the knowledge base used by our hybrid SaaS-LLM application.
Once all the key pieces are in place, we develop a prototype application to review with your team. This is done with the help of AI agents familiar with our key design principles.
The next step is to build the production backend infrastructure required for the application. We do this in either your cloud computing environment or ours using the platform agnostic, highly-scalable Kubernetes architecture. We implement MLOps, LLMOps, and AIOps systems needed for the application in Kubernetes.
Together with setting up the backend infrastructure, we develop the frontend of the application consisting of the conversation agents and familiar software UI starting from the prototype application. These AI agents are continuously improved using the ADLC framework based on user feedback and impact findings.
After thorough testing with your team, we deploy the application so that you can start using Causal AI to improve your organizational outcomes.
Explore applications we have developed for education and water management
Let us show you how the CML+ platform can improve your organizational outcomes with evidence-based intelligence.
Or reach out at info@cmlinsight.com