SLM Fleet Management

Stop Managing Model Files. Start Orchestrating Your SLM Fleet.

Deploying a single LLM is easy. Scaling a fleet of domain-specific Small Language Models across your enterprise is a completely different beast.

Fleet lifecycle

graph TD
  A[Canonical registry] --> B[Gateway routing]
  B --> C[Manifest delivery]
  C --> D[Edge sync]
  D --> E[Zero-downtime rollout]
  E --> F[Rollback and audit trail]

deployed_code

route

memory

model_training

code_blocks

terminal

data_object

dns

commit

device_hub

dashboard_customize

settings_input_component

The canonical model registry

Every SLM is packaged with an immutable model_card.yaml so your team can trace provenance, dataset lineage, hyperparameters, and Git commit history from one source of truth.

Dynamic gateway routing & SemVer

Keep application code free from hardcoded storage paths by routing model access through a gateway that enforces strict semantic versioning, safe major-version checks, and hot-swappable minor updates.

Manifest-based edge delivery

Synchronize edge nodes through compact manifests instead of shipping entire model archives. Delta updates verify cryptographic hashes, download only what changed, and keep local inference pipelines online.

Fleet operations and zero downtime updates

Fleet operations with zero downtime

Hot-swap models in memory, eliminate model rot, automate edge deployments, and keep production services stable while your SLM fleet moves through development, staging, and production tiers.

Is your AI infrastructure suffering from model rot?
The S3 black box is costing you traceability.

When model weights live as static binaries in opaque storage, teams lose the story behind what was trained, why it was promoted, and how it should be deployed safely.

Can your deployment pipeline survive a hot swap?
Zero downtime should be the default.

mbedlm keeps the gateway pattern, semantic versioning, and delta-driven manifest sync in lockstep so updates are verified before they ever touch runtime inference.

Fleet operating rules

Keep the registry canonical and the manifest immutable.
Use gateway routing to avoid hardcoded storage paths.
Prefer delta sync and verification before edge promotion.

Features and tiers built for individual operators and fleet-scale engineering teams.

Features	mbedlm Personal	mbedlm Enterprise
Target audience	Independent developers & researchers	High-throughput engineering teams
Model registry	Up to 5 active models	Unlimited models & historical lineages
Gateway routing	Standard SemVer routing	Premium dynamic routing with A/B testing
Edge syncing	Basic manifest delivery	Advanced delta syncing & full fleet compliance
Support	Community-driven	Dedicated solutions engineer & guided rollout support

Connect fleet operations to full runtime governance

Use fleet management with policy-aware routing, startup validation, and domain adapters to keep model operations aligned with production runtime behavior.

Ready to stop copy-pasting model files and start engineering AI systems?

Join the next generation of AI systems engineering. Bring discipline, speed, and mathematical certainty to your SLM operations today.

Deep Dives

Need implementation depth before rollout?

Explore integration design, runtime operations, and domain workflows from one governed platform narrative.

Integrations Operations Domain Workflows