Client Overview
Industry
Hi-Tech
Region
USA
Company Size
5000+
Featured Solution
Centralized AI Management Platform
Context
The client is a leading global technology company that delivers cutting-edge solutions to enterprises across industries. With a strong presence in both developed and emerging markets, it offers comprehensive end-to-end services encompassing cloud computing, AI, cybersecurity, and digital transformation. As part of its drive to lead in AI adoption, the company utilized multiple Large Language Model (LLM) tools across departments. However, this led to challenges in usage and cost control. Without a unified system, LLM adoption became fragmented and unsupervised. The emergence of critical gaps, such as the absence of PII protection, a lack of audit trails, and frequent disruptions during LLM outages, ultimately pushed the client to seek a solution to manage escalating risks and uncontrolled usage.
Business Challenges
Without centralized oversight, LLM adoption quickly spiraled into:
Fragmented AI Tool Usage
Multiple teams relied on generative AI tools, which overlapped with one another, creating duplication and inefficiency.
Unmonitored Prompt Activity
Prompt runs across Claude, Gemini, GPT-4, and others went unchecked, leading to blind spots.
Uncontrolled Token Spend
Lack of guardrails around token consumption caused costs to spiral unpredictably.
No Unified Visibility
Absence of a central dashboard made it impossible to track usage, costs by model, or performance.
Weak Data Protection & Compliance
No built-in safeguards for PII or audit trails increased regulatory and security risks.
Frequent Service Disruptions
Production workflows stalled whenever LLM providers experienced outages.
The Solution
To regain control over AI usage and costs, the client deployed Grigo, a centralized AI management platform by Grazitti Interactive. This gave them clear visibility and control over LLM adoption across teams.
- Centralized Usage Dashboard
- Consolidated activity across OpenAI, Anthropic, and Google Gemini in one view. This transparency provided the client with real-time visibility into token usage, spend, and model performance, helping them track usage patterns, identify cost drivers, and forecast budget accurately.
- Budget Controls
- Enforced monthly LLM budgets by team and user, with trigger alerts as usage thresholds approached. This prevented budget overruns and curbed runaway token consumption.
- Gateway
- Streamlined application integration, LLM configuration, and budget allocation to accelerate onboarding.
- AI Model & Role-Based Access Control
- Restricted access based on role and team, reducing vendor sprawl and safeguarding sensitive business data from uncontrolled exposure.
- Prompt Testing Playground
- Enabled the client to run side-by-side comparisons of prompts across multiple LLMs before production. This helped them evaluate cost versus quality, standardize prompts, and improve output consistency.
- Secure Access & PII Masking
- By using Grigo, the client was able to detect, mask, and encrypt sensitive data, ensuring compliance with privacy regulations and minimizing exposure risks.
- Knowledge Base with RAG
- Allowed AI to pull data from verified documents, FAQs, and articles, improving the reliability of responses without retraining.
- Chat Interface
- Provided users with a secure, intuitive chat interface to interact with multiple LLMs, ensuring continuity of work even when one model experienced downtime.
Business Outcome
- Centralized visibility and budget enforcement across teams
- Standardized prompts reduced repetition and improved output quality
- Faster experimentation and onboarding with shared prompt libraries
- Better vendor leverage and cost forecasting
- Strengthened data privacy with secure AI tools and PII protection
- No AI service interruptions, even during LLM outages
- Improved auditability and governance across the board
Highlights
25% LLM Cost Reduction in Just 90 Days
Unified AI Oversight Through a Single Dashboard
Improved Governance and Security
Zero Downtime for AI Apps
Conclusion
The client’s journey shows how structured AI management can turn fragmented LLM adoption into a secure, cost-efficient, and scalable practice. If your teams are already experimenting with AI tools but you're struggling to track LLM usage, manage budgets, or enforce secure access to AI assistants, Grigo helps you do it all from one place.
It’s built for enterprises looking to optimize generative AI tools, reduce cost, and stay compliant, without slowing teams down.
Ready to Cut LLM Costs and Strengthen AI Governance With Grigo?
