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ARCby FenxLabsCollective Intelligence

Platform

  • How it works
  • Custom routing and governance
  • Use cases
  • Example architectures

Deployment

  • Hosted Platform
  • Managed Service
  • Self-hosted Licence
  • For ISVs
  • Open the portal

Services

  • Assessment and planning
  • Architecture and integration
  • Model Adaptation
  • EU AI Act readiness
  • Managed Service operations

Resources

  • Cost modeller
  • Compare approaches
  • Pricing
  • FAQ
  • Transparency
  • Get started
  • Discord community

Legal

  • Privacy notice
  • Terms and conditions
  • Sub-processors
  • Accessibility

For individuals

  • FenxChat

FenxLabs. KvK 91762782.

Herengracht 320, 1016 CE Amsterdam, Netherlands

+31 85 060 5273contact@fenxlabs.ai

© 2026 FenxLabs. All rights reserved.

Decide what FenxLabs operates

FenxLabs operates the agreed FenxARC™ and model environment behind your people, applications and agents. Scope can cover routing, model lifecycle, endpoints, incidents, optimisation and reporting. Agent logic and runtime remain with you.

Discuss your requirementsExplore the Managed Service

Available inside your environment or hosted and operated by FenxLabs on your behalf. Scoped to your requirements and quoted per engagement.

Set the operating scope before handover

Each responsibility is agreed for the engagement rather than assumed from a tier. Coverage, response ownership, access and handover are documented before operations begin.

  • AI strategy and operating roadmap
  • ARC and routing operations
  • Model training and inference operations
  • Model updates, onboarding and retirement
  • Endpoint, provider and infrastructure monitoring
  • Incident response responsibility
  • Optimisation, reporting and review cadence
  • Ownership and handover
Over time

Models reviewed as the workload changes

Changing a model changes four things at once: output quality, what the provider charges, which trust boundary the work sits inside, and how much operating effort it carries.

Illustrative scenario
  1. Onboard

    01 / 04

    Bring the model under management

    Add the model to the environment and identify the version that will be managed.

    • Model onboarding
    • Version management

    The registered version moves into evaluation.

  2. Evaluate

    02 / 04

    Check that it still fits the workload

    Review performance and cost before the model enters or remains in operation.

    • Evaluation
    • Performance reviews
    • Cost reviews

    A suitable model moves into live operation.

  3. Operate

    03 / 04

    Keep its live role current

    Update routing policy and optimise the model’s place as the workload changes.

    • Routing-policy updates
    • Continuous optimisation

    A review finding or changing workload can trigger replacement planning.

  4. Retire

    04 / 04

    Replace what no longer fits

    Plan the replacement and retire the endpoint when it no longer suits the workload.

    • Replacement planning
    • Endpoint retirement

    The replacement begins the lifecycle again at onboarding.

Where a review finds a workload no existing or specialised model fits well, that becomes a Model Adaptation decision, not a routing-policy change.
Adapt a model around your data

Ownership and handover stay explicit

Your models, data, routing intent and business accountability remain yours. FenxLabs owns only the operational responsibilities agreed for the engagement.

Handover terms are agreed before operations begin, so your team can take over the documented environment.

Explore the Managed Service

Define the managed service scope

Thirty minutes with an engineer. Your numbers. A straight answer.

Discuss your requirementsExplore the Managed Service