MongoDB Software / SaaS Europe

altermAInd

Security and Compliance

altermAInd needed a database platform that could support fast-moving AI products while preserving governance, GDPR compliance, and strict operational controls in heavily regulated European markets.

10K+ businesses
200K+ customers
Millions of transactions flow through MongoDB Atlas-powered applications every month
launching a fully operational bank—scratch to production—in just eight months

Reported impact

Business outcome

MongoDB Atlas now supports services for over 200,000 retail customers and 10,000 businesses, giving altermAInd the compliant, low-latency data backbone it needs to scale AI governance and monitoring products across Europe.

  • Compliance
  • Scalability
  • Speed to Market

Solution

altermAInd runs its AI platforms on MongoDB Atlas to balance aggressive innovation with European regulatory controls. Atlas underpins Gravity, the company's AI governance platform, and Nebula, its service-level and compliance-monitoring product, by storing real-time operational and model-interaction data in a schema-flexible cloud database that can adapt as products change. Atlas observability, access controls, and data-governance features help the team keep GDPR, the AI Act, and DORA requirements in view while still supporting AI agents, generative interfaces, and rapid product iteration. Because Atlas is fully managed, altermAInd can focus on shipping compliant AI experiences instead of running infrastructure, and the same platform now supports services for more than 200,000 retail customers and 10,000 businesses across Europe.

Data flow

Operational and model-interaction data from Gravity and Nebula flows into MongoDB Atlas, where the schema-flexible store supports real-time governance, service-level monitoring, and AI-agent experiences. Atlas then serves low-latency application access while helping the team enforce access controls and compliance requirements across customers.

Solution architecture

1 components · 1 layer
  1. Storage
    • MongoDB Atlas Stores the real-time operational and model-interaction data behind altermAInd's AI governance and monitoring platforms.

Architecture clues

  • Atlas observability and access controls are used to support GDPR, the AI Act, and DORA requirements.
  • Gravity uses MongoDB Atlas for AI governance in regulated environments.
  • Nebula uses Atlas to collect and manage data for real-time hyperscaler service-level monitoring.
  • The platform is being extended toward vector search and multi-agent AI workloads.

Evidence from the source

Millions of transactions flow through MongoDB Atlas-powered applications every month
MongoDB Atlas powers altermAInd's AI platforms, ensuring real-time data control, GDPR compliance, and scalable innovation for 200K+ customers.
Today, MongoDB Atlas supports services for over 200,000 retail customers and more than 10,000 businesses across Europe.
it's bringing innovation without compromising control or performance
Transparency Evidence & methodology 75/100 reference value · 85% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value75/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence85%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance8/10
    The publication date comes from publisher-controlled metadata.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. MongoDB

    altermAInd customer story

    First-party
    https://www.mongodb.com/solutions/customer-case-studies/altermaind
    Source type
    Vendor-published customer story
    Published
    Sep 10, 2025
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Publisher catalog date Sep 10, 2025 · MongoDB · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.