As enterprises race to turn GenAI pilots into measurable business impact, Arize AI and Infogain have announced a strategic partnership aimed at solving one of AI’s biggest challenges: ensuring complex AI systems actually perform in production.
The collaboration fuses Arize’s AI observability and LLM evaluation platform with Infogain’s Ignis Agentic Platform, an AI innovation engine designed to accelerate enterprise adoption of agent-based systems. Together, the companies are offering a unified toolkit for designing, testing, and scaling AI that delivers real-world results — not just impressive demos.
The Next Phase of Enterprise AI: From Pilots to Production
Every enterprise wants to move from “proof-of-concept” to “profit.” But as large language models and autonomous agents become more complex, maintaining performance, security, and reliability at scale is proving difficult.
Infogain’s Ignis framework provides the orchestration layer — integrating LLMs, APIs, and partner tools to build multi-agent workflows — while Arize AX adds the crucial layer of visibility, evaluation, and real-time monitoring.
“Our clients want AI that performs in the real world, not just in the lab,” said Mohit Bhat, Chief Delivery & Innovation Officer at Infogain. “By bringing Arize AX into the Ignis Agentic Platform, we deliver an end-to-end system that ties AI performance directly to business KPIs.”
What Arize Brings to the Table
Arize AI’s technology acts as the “black box decoder” for AI systems. Its capabilities include:
- Agent Tracing & Replay: Track every model call, decision node, and chain of reasoning across complex agent workflows.
- Evaluations & Online Evals: Continuous, KPI-aligned quality checks to catch regressions before deployment.
- Prompt & Model Optimization: Compare prompts and models across datasets to fine-tune performance.
- Real-Time Monitoring & Alerts: Production observability that connects AI performance to business SLAs.
Coupled with Ignis’ delivery accelerators and AI-first development approach, enterprise teams gain the ability to move faster — without sacrificing security, compliance, or governance.
Why It Matters
AI observability has rapidly emerged as a make-or-break discipline for enterprises deploying GenAI at scale. Tools like Arize AX, Weights & Biases, and LangSmith are becoming essential as companies demand transparency and auditability across multi-model systems.
But Arize’s advantage lies in its independent, framework-agnostic architecture and native support for OpenInference, an open standard it helped create. That makes it easier for teams to unify traces and evaluations across clouds, models, and agent frameworks — an increasingly critical capability in the emerging agentic AI ecosystem.
“Infogain’s Ignis meets enterprises where they are and gets them to value fast,” said Noah Smolen, Head of Partnerships at Arize AI. “Together, we bring the discipline of evaluation and observability to every stage — from discovery to scaled rollout.”
The Bigger Picture
This partnership underscores a growing enterprise trend: AI accountability is becoming as important as AI innovation. As agentic systems start making autonomous decisions, organizations need the same level of rigor in testing and monitoring that’s standard in software engineering.
For both companies, the collaboration extends their reach — Infogain gains a robust observability layer, while Arize deepens its enterprise footprint across multi-agent use cases. The result could be a blueprint for how enterprises operationalize GenAI responsibly, without losing speed or control.
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