Stand-alone Videos

Single demos and walkthroughs. Click a tile to play.

Getting Started

Getting started with the Brutor free trial

Brutor team / May 25, 2026

A quick walk-through of how to download and run the free Brutor.AI trial from trial.brutor.ai — self-host the full platform in your own environment and start governing AI. No credit card needed.

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Product Overview

Brutor AI Platform — Deep-dive for Admins

Martin Bergljung / May 17, 2026

End-to-end walkthrough of the Brutor AI Platform from the admin console to the User Portal — providers, MCP servers, agent skills, knowledge bases, A2A, guardrails, caching, policy-as-code, RBAC, resource groups, API access, and Mission Control.

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Admin How-To

Managing AI Models

Brutor team / May 18, 2026

How AI models are managed in the admin console: connect providers, add models from the built-in catalog, set API keys, tune defaults, and assign each model to the resource groups whose teams should reach it — the foundation every other governance control builds on.

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Admin How-To

Working with MCP Servers

Brutor team / May 21, 2026

Bring tool servers under governance: register an MCP server through the gateway, discover its tools, prompts and resources, bind it to resource groups, and control which capabilities each team can call — then use the tools from the User Portal chat.

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Playlists

Multi-part series that walk a theme end to end. Click a series to see its parts — watch in any order.

6 parts

LLM Governance with Brutor

One OpenAI-compatible API in front of every LLM, MCP, A2A and Skill call your apps and agents make — with guardrails, budgets, RBAC, policy-as-code, a compliance audit trail, cross-vendor cost observability, and out-of-band shadow-AI discovery. Each part walks one capability end to end on a live gateway.

LLM Governance · Part 1

Safety & Guardrails

Brutor team / July 7, 2026

Prompt injection, PII and secrets — stopped at the gateway. A clean prompt hits the semantic cache, an injection attempt is blocked, PII is redacted on output, secrets are caught, and an LLM-judged semantic policy catches intent the pattern rules miss — every event tagged to your compliance frameworks.

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LLM Governance · Part 2

Cost & Limits

Brutor team / July 7, 2026

Make AI spend predictable. Token budgets, per-minute request and token throughput caps, and daily quotas — enforced per team and per model — plus a semantic response cache that turns repeat questions into near-instant, near-free hits. Hit a cap and the gateway returns a clean 429, not a surprise bill.

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LLM Governance · Part 3

Access & Resilience

Brutor team / July 7, 2026

Access that’s structural, and uptime that survives a provider outage. Resource-group RBAC (each team reaches only its own models, refused by name), weighted model routing groups, and automatic failover: when the primary returns a 401 the router retries a secondary and the user never notices — both legs on the audit trail.

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LLM Governance · Part 4

Govern & Prove

Brutor team / July 7, 2026

Where enforcement becomes evidence. An argument policy denies a destructive SQL tool call, then the policy-as-code lifecycle (export → dry-run → promote a versioned bundle), a compliance dashboard where every call is tagged at write-time (EU AI Act, SOC 2), and the AI Asset Registry fact sheet — one asset’s full governance record.

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LLM Governance · Part 5

Observe What You Can’t Govern

Brutor team / July 7, 2026

The honest boundary. Your people use Claude Desktop, ChatGPT and Gemini on company accounts — traffic no gateway is in the path of. Part 5 imports that usage and cost from the vendor’s analytics API into one ledger: flip Mission Control’s Governed / Observed / All plane and the totals span the whole estate, per product and per person.

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LLM Governance · Part 6

Discover Shadow AI

Brutor team / July 7, 2026

Find the AI nobody sanctioned. The Shadow AI Discovery SDK: out-of-band collectors and ingest adapters (CycloneDX AI-BOM, Snyk agent-scan / mcp-scan, AgentSonar, SafeDep vet) emit Ed25519-signed discovery events. The platform reconciles each against its route table, flags ungoverned endpoints and agent stacks, then onboards one into governance in a click.

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3 parts

MCP Governance with Brutor

Governing the tool layer: one live MCP server, six tools — filtered per team, argument-checked by real parsers, redacted, rate-limited, approval-gated, intent-judged by an LLM, and fully audited. Three parts, from the everyday golden path to the control room.

MCP Governance · Part 1

Golden Path & Guardrails

Brutor team / July 10, 2026

One server, six tools — filtered per team at the gateway, not in the client. The golden path returns real rows; a destructive DELETE is parsed by a real SQL analyzer and refused even after the user approves it; and a customer record comes back with PII redacted by Microsoft Presidio and leaked credentials masked — every call one audit row.

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MCP Governance · Part 2

Access & Limits

Brutor team / July 10, 2026

Who can call which tool, how often — and which calls need a human. Per-team capability filters, a gateway-held approval for send_email (one-shot token; a replay is refused), a per-tool rate limit that turns the third expensive report of the hour into a clean 429, SSRF protection on fetch_url, and a shell-parser command allowlist on the Ops host.

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MCP Governance · Part 3

Govern & Observe

Brutor team / July 10, 2026

Beyond structure: what comes back, and what a call means. Category-aware secrets detection blocks a tool result leaking a GitHub token and an AWS key; an LLM-judge semantic policy blocks a comment-injection the AST parser waves through; Mission Control counts every block on the governance ledger; and the AI Asset Registry plus compliance tagging turn it into auditor evidence.

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4 parts

Agent Skills Governance with Brutor

Agent Skills are reusable, versioned units of work — a SKILL.md prompt plus a sandboxed script — that the gateway hosts, runs, and exposes to agents as governed tools. Four parts: an introduction to the architecture and runtime; a gentle Hello World where an end user simply asks in chat and the AI discovers, loads and runs the skill; then setup and guardrails; then argument policies, per-skill quotas and human approval.

Agent Skills Governance · Intro

Introduction: Architecture & Runtime

Brutor team / July 13, 2026

What an Agent Skill is, and how Brutor governs it. A skill is a SKILL.md prompt plus a sandboxed script — hosted by the gateway and exposed to agents as a system MCP tool, so the same guardrails, policies and audit trail that govern LLM and MCP calls govern skills too. Covers the two hosting models (upload a package, or sync from GitHub), how a skill executes in the runner, and where each control sits.

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Agent Skills Governance · Part 1

Hello World

Brutor team / July 15, 2026

The gentlest possible start. Publish a skill and assign it to a workspace, then a Sales rep simply asks the portal chat for a greeting — and the AI works through progressive disclosure: it discovers the skill, loads its instructions, runs the sandboxed script to gather system information, and renders the greeting template. The rep never sees a tool or a script, and every step is a separate, access-scoped, audited call.

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Agent Skills Governance · Part 2

Setup & Guardrails

Brutor team / July 15, 2026

Configure a skill, decide who can run it, then watch the gateway govern every call. Config-first: the skill catalog, binding skills to a resource group with keys and members, and the guardrails and argument policy bound to that group. Then live — a read-only report runs (202, async, audited); the same call from a team without access is denied; PII in a skill’s input is blocked before the sandbox runs; and PII in its output is redacted. Every outcome a full audit row.

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Agent Skills Governance · Part 3

Policy, Limits & Approval

Brutor team / July 15, 2026

The deeper controls, enforced live. An argument policy parses a skill’s SQL input into a syntax tree and refuses a destructive write with the exact rule that fired; a per-skill daily execution quota returns a clean 403 on the run past the cap; and a high-blast-radius skill is parked as PENDING until a human approves, with a one-shot token that releases exactly one execution — each refusal on the record and tagged to your compliance frameworks.

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5 videos

Agent Governance with Brutor

The finale, where the model, tool and skill stories come together. One example agent system — the ACME Revenue Copilot — modelled as an AI System (an ISO 42001 AI system; in Brutor a resource group of type ai_system) that owns every resource it uses. An introduction sets up the system and the concepts, then four standalone demos govern it: the AI System itself, identity & authorization, the A2A network, and observability.

Agent Governance · Intro

Introduction: The AI System

Brutor team / July 11, 2026

Where the model, tool and skill series come together: an agent is all of those at once, acting on its own — an AI System in the ISO 42001 sense. Meet the example ACME Revenue Copilot with a full architecture diagram, then the core concepts: identity vs. signed cards, allow / deny / approval authorization layered with an LLM-judged intent policy, and the governed agent-to-agent network.

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Agent Governance · Part 1

AI Systems

Brutor team / July 11, 2026

One agent system, one AI-System resource group that owns every resource it uses — the reasoning model, the MCP tool server and the Agent Skills system server that runs skills as tools, a published skill, the agent identity and its peer cards. The key distinction, made explicit: an identity is the caller; a card is a signed listing of a callee — all access-controlled to the one system, with its guardrails and policies attached.

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Agent Governance · Part 2

Identity & Authorization

Brutor team / July 11, 2026

Give every agent an identity, then authorize what it may do. Open the Data Export Worker — a machine principal with a SPIFFE workload subject and a default-deny baseline — and read its grants like a sentence. On the wire: an ungranted tool is refused 403 before it runs, an approval-required tool parks at 202 with a poll URL, and the granted call just works — each an audit row carrying the identity, the decision and the grant.

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Agent Governance · Part 3

The Network (A2A)

Brutor team / July 11, 2026

Agents calling agents, safely. Signed Ed25519 cards verified against a published key, per-system access (an outside key is refused), guardrails both ways (inbound PII blocked at the door, outbound redacted on the wire), a per-AI-System egress policy that denies a PII-classified capability outright, and a cryptographic delegation chain with a depth cap that refuses a forged hop — every call on the audit log.

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Agent Governance · Part 4

Observability

Brutor team / July 11, 2026

You can’t govern what you can’t see. The AI Asset Registry now inventories the whole picture — models, MCP servers, skills and cards, and the AI System and agent principals themselves — each with a one-page fact sheet. Mission Control counts every guardrail block, the AI System’s own Usage tab rolls up every surface into one combined view, and delegation graphs reconstruct each multi-agent workflow as a named, signed tree.

Videos

Brutor.AI Videos

Stand-alone Videos

Getting started with the Brutor free trial

Brutor AI Platform — Deep-dive for Admins

Managing AI Models

Working with MCP Servers

Playlists

LLM Governance with Brutor

Safety & Guardrails

Cost & Limits

Access & Resilience

Govern & Prove

Observe What You Can’t Govern

Discover Shadow AI

MCP Governance with Brutor

Golden Path & Guardrails

Access & Limits

Govern & Observe

Agent Skills Governance with Brutor

Introduction: Architecture & Runtime

Hello World

Setup & Guardrails

Policy, Limits & Approval

Agent Governance with Brutor

Introduction: The AI System

AI Systems

Identity & Authorization

The Network (A2A)

Observability

AI is everywhere in your organization — your control over it will be too.