Skip to content
MibonoIntelligence

Plan and execute AI workloads

MeshAI

Plan, place and execute AI workloads efficiently across any compute.

The problem

AI compute decisions are expensive and hard to reverse. Organisations over-provision, under-utilise, or place workloads where power, connectivity or sovereignty rules make them fragile.

What MeshAI does

  • Models workload demand before you commit to capacity.
  • Selects and places workloads across owned, rented, hosted, cloud, local and edge compute.
  • Runs inference efficiently and keeps utilisation high.
  • Accounts for power, connectivity, resilience and sovereignty.

Scenario

Illustrative scenario: in-country inference

Illustrative example, not a customer deployment.

  1. 01Demand is modelled for a document-processing workload.
  2. 02Sensitive workloads are placed on customer-owned servers in-country.
  3. 03Burst demand is placed on a hosted provider.
  4. 04Branch sites run small models at the edge during connectivity outages.
  5. 05Cost per successful inference is reported per placement.

Key capabilities

What you get with MeshAI

  • Workload demand modelling
  • Infrastructure selection and placement
  • Capacity planning and utilisation
  • Efficient model serving
  • Resilience, power and connectivity awareness
  • Sovereignty-aware placement
  • Cost per successful inference

Your infrastructure or a third party's

MeshAI works on infrastructure you own or infrastructure supplied by a third party. You do not need to buy hardware from Mibono.

How MeshAI is charged

Infrastructure charges — paid to whoever supplies the compute, which may be you, a host or a cloud provider.

MeshAI subscription — for the planning and execution platform.

Optional managed services — if you want Mibono to operate and optimise the environment.

Relationship with MIP

MIP can show where every workload runs and what it costs — whether on MeshAI or third-party infrastructure — and apply authorised placement changes through MeshAI.

About MIP →

Consulting starting point

See MeshAI against your scenario.

We demonstrate on a problem you describe, not a generic script.

Request a demonstration