Poisontune Launches Agent-First AI Platform to Help Enterprises Deploy Custom AI at Scale

Los Angeles, CA - Jan 6

Poisontune, a new AI infrastructure platform, today announced the launch of its agent-first system designed to help enterprises build, deploy, and scale custom AI agents using their own proprietary data - without the operational complexity traditionally associated with machine learning.

As organizations race to adopt AI, many struggle with fragmented tools, high deployment costs, and unreliable outputs. Poisontune addresses this gap by offering an end-to-end platform that transforms internal knowledge into production-ready AI agents, accessible through secure APIs and optimized for real-world use cases.

"AI adoption shouldn't require companies to become ML labs," said the CEO of Poisontune. "Our goal is to let teams focus on outcomes - customer support, internal automation, analytics, and decision-making - while Poisontune handles the heavy lifting behind the scenes."

An Agent-First Approach
Unlike traditional fine-tuning platforms, Poisontune is built around complete AI agents, not just models. Each agent integrates retrieval-augmented generation (RAG), behavior controls, memory, evaluation pipelines, and monitoring from day one - ensuring reliability, transparency, and scalability.
Key capabilities include:
Multi-model support, enabling teams to choose the best-fit LLM for each workload
Secure knowledge ingestion, allowing enterprises to safely use internal data
Automated evaluation and deployment, reducing time from prototype to production API-first architecture, making integration seamless across products and workflows Designed for Enterprise Scale.

Poisontune is purpose-built for companies moving beyond experimentation into full production. By abstracting infrastructure complexity, the platform helps organizations reduce operational overhead while maintaining control over performance, costs, and governance.

Early adopters report faster deployment cycles, improved AI reliability, and greater confidence in using AI across mission-critical workflows.
Looking Ahead With growing demand for trustworthy, scalable AI systems, Poisontune aims to become a foundational layer for enterprise AI - empowering teams to deploy intelligent agents that are aligned with business goals and grounded in real data.

Poisontune is currently onboarding select partners and enterprise customers.
About Poisontune.

Poisontune is an AI infrastructure company focused on enabling organizations to build and deploy custom AI agents using their own data. By combining modern language models with retrieval, evaluation, and deployment tooling, Poisontune helps enterprises move from AI experimentation to real-world impact.

Media Contact:
Press Team
hello@poisontune.sbs

PoisonTune
12, Post Street, LA, CA
7056221176, Founder (Manmohan Yadav)
Press Contact: hello@poisontune.sbs, +91 7056221176, Dr. S. Abelzek

Detailed Conception of the Enterprise
Poisontune is an agent-first AI infrastructure enterprise designed to enable organizations to securely transform their proprietary data into production-ready artificial intelligence agents. The enterprise addresses a critical challenge faced by modern organizations: while large language models have become powerful and widely accessible, deploying them reliably, securely, and cost-effectively in real business environments remains complex.
Poisontune's conception is rooted in the belief that AI value is created not at the model layer, but at the agent layer, where data, reasoning, tools, and governance converge. Instead of offering isolated model fine-tuning or experimental AI workflows, Poisontune provides a unified platform that orchestrates the entire lifecycle of AI agents - from knowledge ingestion and behavior design to evaluation, deployment, and monitoring.
The enterprise is architected to support multi-model interoperability, allowing organizations to select the most appropriate language model for each use case while maintaining consistent performance, security, and operational controls. By abstracting infrastructure complexity, Poisontune enables teams across industries to adopt AI without requiring specialized machine-learning expertise.
At its core, Poisontune is conceived as a foundational AI layer for enterprises transitioning from pilot projects to large-scale AI adoption. The platform emphasizes reliability, transparency, and scalability, ensuring that AI agents remain aligned with organizational objectives, data governance requirements, and performance expectations.
Description of the Enterprises Involved
Poisontune (Primary Enterprise)
Poisontune operates as the central enterprise responsible for the development, operation, and continuous improvement of the AI agent platform. Its key responsibilities include:
Designing and maintaining the agent-first architecture
Managing secure data ingestion and retrieval systems
Enabling model orchestration across multiple LLM providers
Providing deployment, monitoring, and evaluation infrastructure
Ensuring enterprise-grade reliability, governance, and scalability
Poisontune functions as both a technology provider and AI infrastructure partner, supporting organizations across diverse sectors such as technology, finance, healthcare, education, and enterprise services.
Client Enterprises (Adopting Organizations)
Client enterprises consist of organizations seeking to deploy AI agents using their internal data for operational, analytical, or customer-facing applications. These enterprises leverage Poisontune to:
Convert proprietary knowledge into actionable AI systems
Deploy AI agents via APIs across internal tools and customer platforms
Maintain control over data access, performance, and cost
Reduce time and complexity associated with AI deployment
By utilizing Poisontune, client enterprises can focus on business outcomes while relying on a standardized, secure AI foundation.
Technology Ecosystem Partners
Poisontune integrates with a broader ecosystem of AI model providers, cloud infrastructure platforms, and enterprise software systems. These partnerships enable flexibility, resilience, and future-proofing by ensuring that organizations are not locked into a single model or vendor.
Enterprise Value Proposition (Summary)
Agent-centric AI adoption rather than model experimentation
Enterprise-ready deployment with governance and monitoring
Reduced operational complexity and faster time to value
Scalable foundation for long-term AI transformation

This release was published on openPR.