---
title: "Building AI You Can Trust: Bigeye’s New Technical Lead Shows What Enterprises Need Next"
description: Bigeye prioritises AI trust and data observability with key executive hires, addressing enterprise AI governance, compliance and transparency challenges
author: Darie Nani (Editor-in-Chief)
date: 2025-06-27T12:04:15.000Z
updated: 2026-02-25T15:38:43.603Z
canonical: https://www.sovereignmagazine.com/article/building-ai-you-can-trust-bigeye-s-new-technical-lead-shows-what-enterprises-need-next
image: https://cdn.nanimediahouse.com/eym7np5kszw.jpg
categories: Business
content_type: Spotlight
region: United States
publication: Sovereign Magazine
about:
  - type: Person
    name: Mohamed K. Alimi
---

Companies rushing to adopt AI face an uncomfortable reality: most worry more about whether their AI systems can be trusted than what they can accomplish. As enterprises grapple with [managing large data volumes](https://cloudsecurityalliance.org/blog/2025/04/22/ai-and-privacy-2024-to-2025-embracing-the-future-of-global-legal-developments) with real-time policy enforcement and building AI transparency to address trust issues, their hiring decisions reveal priorities that extend far beyond product features.

Bigeye’s decision to appoint Mohamed K. Alimi as Vice President of Engineering signals how companies are now staffing up to address trust as much as capability. The data observability company’s choice of leadership shows a shift from talking about AI governance to actually building the infrastructure that makes it possible.

## What Enterprises Actually Need

Bigeye’s AI Trust Platform aims to monitor how AI agents use enterprise data, ensuring AI systems interact with company information responsibly. The platform promises to bring transparency and observability to AI data usage – addressing what [IBM research identifies](https://www.ibm.com/thought-leadership/institute-business-value/en-us/report/ai-governance) as key challenges including compliance risks, data bias and trust issues that enterprises face as AI adoption accelerates.

The technical backgrounds of first hires often reveal how seriously a company will tackle complex governance questions. Yet as [recent safety controversies at major tech firms](https://www.sovereignmagazine.com/article/controversy-erupts-over-safety-of-ai-models-in-top-tech-firms) show, promises of AI safety don’t always translate to practical monitoring tools that work at enterprise scale.

## Why This Hire Matters

Alimi arrives with experience building real-time visibility systems for AI applications. He led the team behind [Datadog’s LLM Observability product](https://www.datadoghq.com/blog/datadog-llm-observability/), which moved from initial research to market launch in under nine months. His previous work at Amazon and Datadog focused on monitoring and troubleshooting AI systems – exactly the experience needed for enterprise-scale AI governance.

‘Mohamed’s experience building real-time visibility into AI systems makes him an ideal partner as we move from concept to execution,’ said Eleanor Treharne-Jones, CEO of Bigeye.

This type of hire signals that Bigeye recognises the difference between promising AI governance and actually delivering tools that work for large, data-driven companies with complex compliance requirements. The trend mirrors [broader patterns in tech hiring](https://www.sovereignmagazine.com/article/top-engineering-appointments-drive-surge-in-demand-for-metaverse-development-expertise) where companies prioritise proven technical execution over theoretical expertise.

## Beyond Monitoring Buzzwords

The AI Trust Platform represents an extension of Bigeye’s existing data observability work. The company already supports enterprises globally with [clients including Instacart, USAA and Udacity](https://www.bigeye.com/resources), providing automated data quality monitoring and machine learning-powered anomaly detection.

Bigeye’s current products demonstrate practical applications: [Dependency Driven Monitoring](https://www.sovereignmagazine.com/article/bigeye-bets-on-ai-trust-platforms-as-mohamed-k-alimi-joins-to-build-agent-oversight-tools) maps how data flows through enterprise systems, while AI-powered anomaly detection identifies when data quality issues might affect downstream applications. These tools address the foundation layer that reliable AI systems require.

## The Real Enterprise Challenge

Alimi’s perspective highlights the gap between AI adoption pressure and practical implementation tools. ‘Enterprises are under pressure to adopt AI faster, but most don’t have the tooling to manage it reliably,’ he said. [Bigeye is building the foundation](https://www.sovereignmagazine.com/article/google-s-defence-architects-launch-aegisai-ai-native-email-security-as-phishing-attacks-quadr) that will make AI adoption both safe and scalable for enterprises.’

This matches what [enterprise security research](https://www.kiteworks.com/cybersecurity-risk-management/ai-agents-enterprise-data-privacy-security-balance/) shows: companies adopting AI agents face significant data privacy and trust challenges that require secure layers governing AI agent data access, logging and policy enforcement. The situation reflects broader issues with [enterprise AI integration](https://www.sovereignmagazine.com/article/enterprise-knowledge-management-enters-new-era-as-ai-integration-accelerates) across business systems.

Without proper monitoring and governance frameworks, enterprises risk compliance violations, data breaches and AI systems that make decisions based on unreliable information. The consequences extend beyond technical problems to regulatory penalties and damaged customer relationships.

## Scaling Technical Capability

Bigeye’s hiring signals preparation for the AI Trust Platform’s first release later this year. The company is actively recruiting across engineering and product functions, prioritising technical execution over marketing promises.

‘This is an [extension of data observability](https://www.sovereignmagazine.com/article/unifyapps-raises-50m-to-clean-up-enterprise-ai-s-40bn-graveyard), and a whole new layer in the AI tool stack that enterprises will need to safely scale up their use of agents,’ said Kyle Kirwan, Bigeye’s co-founder.

The hiring approach reflects recognition that [visionary leadership in AI-driven companies](https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work) requires both technical credibility and executive capabilities to bridge the gap between product development and business needs.

## What Buyers Should Watch

For enterprise buyers evaluating AI vendors, leadership appointments offer insights into how seriously companies approach governance challenges. Technical leaders with hands-on experience building [AI observability systems](https://opentelemetry.io/blog/2025/ai-agent-observability/) understand the complexity of monitoring AI agent behaviours and ensuring compliance at scale.

The difference between companies that talk about AI trust and those that build reliable tools often shows up in their hiring decisions. Leadership moves deserve as much attention as product launches when evaluating AI vendors and their ability to deliver on governance commitments.