Thursday, January 15, 2026
GoML, a leading generative AI development company, has introduced AI Matic, a groundbreaking production-first framework that helps enterprises and startups move seamlessly from pilot projects to full-scale, production-ready AI systems.
As organizations across industries ramp up their investments in generative AI, many still struggle to scale beyond the proof-of-concept phase. According to industry insights, a large number of enterprise AI initiatives fail to reach production due to challenges like low adoption, limited accuracy, and infrastructure complexity.
To address this gap, GoML developed AI Matic — a comprehensive, AWS-native solution that enables companies to operationalize AI safely, efficiently, and at scale.
“Every enterprise wants to get Gen AI into production - but most are held back by complexity, not capability,” said Rishabh Sood, Founder of GoML. “AI Matic removes that friction. It brings structure, predictability, and speed to how AI is deployed and scaled. The result is a faster route to ROI and a higher rate of real-world adoption.”
Drawing from its experience across more than 130 enterprise AI implementations, GoML designed AI Matic to dramatically cut deployment timelines. What typically takes 12 to 18 months can now be completed in just 2 to 12 weeks.
The framework combines pre-built LLM modules, data engineering blueprints, compliance guardrails, and Amazon Bedrock-based architectures with LLMOps best practices. This unique setup allows enterprises to accelerate pilot programs while ensuring they’re production-ready from the start.
At its core, AI Matic features six ready-to-deploy accelerators covering the most common enterprise AI applications:
Content generation
Conversational agents
Data analytics and insights
Enterprise search
Data synthesis
Each accelerator includes built-in templates for integration, observability, and governance — allowing companies to launch with confidence and minimal risk.
AI Matic is central to GoML’s mission to make enterprise AI operational from day one. Built upon the company’s architectural best practices for Amazon Bedrock and AgentCore, it ensures flexibility, scalability, and security without vendor lock-in.
“Enterprises are long past the time for experimenting with more and more pilots. What they need is AI that performs magnificently in real-world conditions,” added Sood. “AI Matic bridges that gap. It’s how we’re helping our customers move beyond experimentation and into true AI-led transformation.”
For startups and mid-market enterprises, AI Matic delivers a cost-effective way to speed up AI adoption. By simplifying orchestration and infrastructure management, it lets teams focus on business outcomes rather than backend development.
For large enterprises, it offers a standardized, compliant framework to streamline governance across multiple AI projects — ensuring consistent quality and compliance.
Early GoML customers have already reported impressive results with the AI Matic framework, including:
80% faster time-to-market
60% lower development costs
Up to 95% reduction in deployment failure risk
These measurable outcomes demonstrate how AI Matic can transform the way businesses approach AI deployment, bringing scalability, reliability, and agility to the forefront.
For CIOs and CTOs, AI Matic provides a structured pathway for AI adoption—from discovery and pilot stages to compliant, production-grade deployments—paving the way for sustainable innovation.
To join our expert panel discussions, reach out to info@intentamplify.com
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