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Galini

Y Combinator LogoF24
Active
artificial-intelligence
saas
b2b
compliance
enterprise
San Francisco
 
https://www.galini.ai/

Compliance guardrails-as-a-service for AI applications

Galini guardrails-as-a-service filter harmful inputs and outputs based on company policies and industry regulations. We make it easy for enterprises to create, test, deploy and refine guardrails. With Galini, product and engineering leaders enjoy peace of mind knowing their AI apps are compliant at run-time, and save $1-10M in costs from avoiding in-house build
Galini
Founded:2024
Team Size:2
Status:
Active
Location:San Francisco
Group Partner:Diana Hu
 
Active Founders

Shaun Ayrton, Founder, CEO

Cofounder and CEO of Galini. Prior to Galini, Shaun was a sr. engagement manager at McKinsey where he drove $500M+ revenue growth for F50 software and telecom companies. He developed the GTM plan from pre launch to $1B in revenue for a conversational AI leader and drove an additional $50M in annual revenue for a regional telco while the industry is declining at 3%, each acquired for ~$20B. He has an MBA from Wharton and a dual degree in computer science and Finance at UPenn (M&T)
Shaun Ayrton
Shaun Ayrton
Galini
 

Raul Zablah, Founder

Cofounder and CTO of Galini. Prior to Galini, Raul was a sr. staff engineer at Ridgeline where he built the SRE team from 0 to 10 supporting 10x customer growth in 12 months (reporting to the CTO for a 350 engineer org). Before this, he was the tech lead for the SRE team responsible for $175B AUM investment engine at Bridgewater where he built the team from 0 to 6 and established SRE best practices for an org of 300 engineers. He has a masters in computer science and dual degree from UPenn
Raul Zablah
Raul Zablah
Galini
 
Company Launches
Galini - Compliance guardrails for AI applications
See original launch post ›

Hey everyone, we’re Shaun and Raul - cofounders of Galini.

TL;DR

Galini guardrails filter harmful inputs and outputs based on company policies and industry regulations. We make it easy for companies to create, evaluate, deploy and monitor guardrails.

With Galini, product and engineering leaders enjoy peace of mind knowing their AI apps are compliant at run-time, and save $1-10M from avoiding an in-house build.

Ask: If you are building or using AI applications, let us take run-time compliance off your plate. Email founders@galini.ai or please refer us to others who may need this.

Watch our demo here

❌ The Problem:

Compliance and trust are major barriers to scaling AI, with one in two executives fearing reputational damage.

Ignoring the problem does not make it go away: A staggering 44% of organizations have reported negative consequences from using AI chatbots and assistants.

The cost of non-compliance is rising: Fines of 7% annual revenues (or 35M EUR) for non-compliance with EU AI Act; similar regulations are fast approaching in the US.

Companies are not ready: Only 6% feel ready to accommodate these changes, while 80% are committing 10%+ of their AI budgets to compliance.

✅ Use cases:

Most customer- or employee-facing AI applications require guardrails:

  • Search: Block non-compliant queries and prevent exposing sensitive or proprietary information to users.
  • Chatbots: Ensure responses are accurate and compliant with company policies.
  • Assistants: Stop misleading advice in violation with company policies that could cause negative PR or legal risks.
  • Agents: Control scope and prevent unauthorized actions or transactions.
  • Recommendation engines: Filter outputs to avoid biased, irrelevant or offensive suggestions that damage brand trust.
  • Decisioning systems: Ensure automated decisions (e.g., loan approvals, hiring) meet regulatory standards and prevent discriminatory outcomes.

No enterprise-grade guardrail solutions exist today. Companies incur $1-10M+ in costs annually and 6-12 months in delays building guardrails in-house.

🎯 The Solution: Galini to the rescue

Galini’s guardrails as-a-service enforces runtime compliance with four core modules:

  1. Build custom guardrails based on your company’ policies

  2. Evaluate your guardrails using Galini’s synthetic test generator and evaluation engine

  3. Deploy into your app in seconds with our API

  4. Monitor and improve performance by providing feedback to Galini’s agent

🙏 Our ask:

  • Follow us on LinkedIn, and book a demo with our team
  • Share this post! Do you know product and engineering leaders in regulated industries like finance, healthcare, education and public safety? Please share this post; we’ll save them 1000+ hours in dev costs and many sleepless nights!
  • Learn more at Galini.ai Please reach out to founders@galini.ai

🤝 The team:

Shaun Ayrton (CEO) – A former McKinsey leader, Shaun drove $500M+ in revenue acceleration at leading global software and telecom clients. He witnessed firsthand how companies struggle to manage the risks of AI deployment.

Raul Zablah (CTO) - As a former senior staff engineer, Raul has built and scaled industry-leading enterprise platforms at Bridgewater, Morgan Stanley and Ridgeline and has published papers in the field. His specialization is SRE and making technology work securely and reliably at enterprise scale.

Shaun and Raul met on their first day at UPenn’s M&T program in 2011 and have been dear friends since.