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Bud AI Foundry · Layer 04 · Deployment & Serving

The all-in-one control panel for enterprise GenAI.

The 40-tool GenAI stack is the problem, not the baseline. AI Foundry replaces it with one control panel — maximum infrastructure performance, minimum total cost of ownership, and end-to-end control from deployment to compliance. Hybrid by default.

Overview

One serving plane for production GenAI.

Inference, guardrails, observability, evaluations, identity, and FinOps — optimized together so your AI initiative runs as a profit center, not a cost center.

  • Bud AI Foundry is Layer 04 of the eight-layer Bud stack — the Deployment and Serving layer. The operational layer across inference, guardrails and agents; hybrid by default. One plane for inference, guardrails, agents and observability; hybrid AI layer with on-prem and cloud models behind one API; Bud Runtime scale-out across CPU, GPU, HPU and NPU; SLO auto-parallelism, LoRA hot-swap, 40–60% less waste.
  • One serving plane: a request flows through auto performance optimization (about 3×, 12× faster cold starts, sub-1ms gateway), serving-time guardrails (300+ probes, SENTRY), cost-aware routing and FinOps (up to 6× better TCO), observability (latency, cost, accuracy), evaluations (300+ benchmarks, A/B), and zero-config scale (12+ clouds, scale-to-zero) — resolving as governed output.
  • Six capability groups inside the plane: auto performance optimization; cost optimization and FinOps; guardrails at serving time; observability and SLO tracking; evaluations and experiments; zero-config scale.
  • The result: a profit center, not a cost center.
Value proposition

Forty tools become one control panel — and AI becomes a profit center.

Maximum infrastructure performance, minimum total cost of ownership, and end-to-end control from deployment to compliance. Because inference, guardrails, cost, and observability are optimized together — not stitched across point tools — the gains compound instead of cancelling out.

GPU throughput~3×
Cold starts12× faster
Gateway overhead<1ms
Total cost of ownershipup to 6× better
vs. naïve serving baselines · methodology in the product brief
Key features

Six things only the whole plane can do.

Point tools each do one slice. These come from inference, guardrails, cost, and observability living on one plane — and they're why Bud AI Foundry replaces the forty-tool stack instead of joining it.

01

Automated golden path

Onboard → govern → evaluate → size → deploy → serve — the whole path from registry to governed production, automated.

9 stepsregistry → governed serving · one flow
02

Auto performance optimization

Per-model parallelism, quantization, and execution — chosen for you, per workload and hardware.

~3× GPU throughput12× faster cold starts · <1ms gateway
03

Unbypassable policy plane

Every request crosses the sub-millisecond gateway — guardrails, identity, and audit enforced at one point.

300+ probesevery request · one policy point
04

Cost as a first-class surface

Cost-aware routing, budgets and rate limits per project, team, and agent — hardware sized before you spend.

up to 6× better TCOvs. a GPU-only single tier · same SLA
05

Sovereign by design

Runs in your perimeter on hardware you own — air-gapped included. No vendor or accelerator lock-in.

0 external depsyour perimeter · air-gapped ready
06

Frictionless migration

OpenAI-compatible APIs and SDKs mean existing clients move to Foundry without a rewrite.

~0 switching costswap a base URL · keep your clients
Featured components

What's inside the control panel.

Foundry is built from named components across its cooperating planes. The six evaluators ask about most — the full inventory is in the product brief.

Data plane

Bud Runtime

The universal inference engine — auto parallelism, quantization, and execution across CPU, GPU, HPU, and NPU.

one runtime · any accelerator
Data plane

Bud Gateway

The standards-compatible data plane every request travels — routing, auth, and policy enforcement in under a millisecond.

<1ms added p99
Routing plane

Semantic Router

Directs traffic across SLMs, LLMs, and hardware tiers by cost and SLO — the engine behind hybrid-by-default.

cost- & SLO-aware
Control plane

BudSimulator

The sizing engine — models your workload and picks cost-optimal hardware and serving settings before you deploy.

sized before you spend
Agent plane

Agent Runtime

Tool-using execution for agent workloads, with a Secure Sandbox and Document Engine built in.

sandboxed by default
Component page

Bud Sentinel

The guardrail engine inside Bud SENTRY — scans every inbound and outbound request at serving time, CPU-native.

0.70ms p50 · 300+ probes
Go deeper

The full story, in depth.

The architecture, benchmarks, and methodology behind the claims, in full.

Get started with Bud

Put your data on it.

The fastest way to see what an integrated AI operating system does for your enterprise is a proof-of-concept on your infrastructure, with your data.

01 Identify a use case where complexity, cost, or governance is a known pain point.
02 Joint discovery — Bud maps your AI pain points to platform capabilities.
03 POC in days, on your hardware, with your data.