Most teams are stuck fighting the same three problems before they ship anything.
Every request hits the same expensive model whether it needs to or not — bills climb long before usage does.
Teams spend months wiring APIs, writing routing logic, and building the observability layer before they can trust it.
GDPR and audit requirements get bolted on after launch — when they should be the foundation.
Type what you want in a sentence. SentinelMesh designs the flowchart (AI steps, branches, app actions), checks every step, and hands you a draft you can edit and test.
Observability, explainability, and governance built in from the start. Every routing decision is tracked, every model is monitored, and every outcome can be explained.
A bandit algorithm, Q-learning, and a world model work together to pick the best model for every request — learning from production traffic to keep improving the cost/quality tradeoff.
Request-level tracing, per-model performance, cost, and latency — one dashboard shows every routing decision and cache hit across your stack.
Every model selection ships with its reasoning: confidence score, routing rationale, and cost analysis — an audit trail built for compliance, not added for it.
Stop wiring LLMs to APIs by hand. SentinelMesh agents get a tool belt — search, databases, Slack, calculations — and the judgment to decide what to use and when.
You define a tool.
You hand it to an agent.
You call agent.run("task").
Tools like n8n and Zapier have you build the flowchart yourself, node by node. Here you describe it, get the flowchart, and edit only what you want to change.
Every trained model belongs to your company, not us. Take it with you at any time.
Download your trained model weights as an archive and run them on your own infrastructure — no dependency on SentinelMesh.
One call wipes every interaction your company ever sent us — GDPR Article 17 compliant.
Force external LLMs, force internal models, or let the independence scheduler decide. You choose.
A five-stage path that progressively shifts you from paying per token to running your own models.
Route requests through SentinelMesh to any external LLM. Every response becomes training data — tenant-scoped, never mixed.
After 1,000 high-quality interactions, SentinelMesh trains your first models via knowledge distillation. You own these outright.
The independence scheduler uses confidence scoring to decide when your internal model is ready to answer — no manual intervention.
As accuracy improves, self-model usage grows in stages. Each stage cuts cost proportionally.
At full maturity, most requests run on your own models. Export them, self-host, or run on-premise.
Every connector below makes a genuine call to its vendor's API — configure it with real credentials and it does the real thing.
How teams across industries put SentinelMesh to work.
Automate cross-department workflows and cut per-task cost by routing to the cheapest model that meets your quality bar.
Automate customer service, personalize recommendations, and monitor inventory with agents that reach your real systems.
A GDPR-minded platform for scheduling, administrative work, and patient communication with a full audit trail.
is all it takes to get a working draft agent — model, system prompt, and settings generated for you, ready to test.
is logged with the real model used, the real cost, and the real latency — no black box, no guessing.
on the models you train — export the weights and run them anywhere, anytime, on your own infrastructure.
No credit card required. Describe it, then test it.