ActionBoard doesn't overwhelm you with everything at once. As your AI execution history deepens, new formation patterns, agent configurations, and automation capabilities unlock, calibrated to your actual AIOps maturity, not your subscription tier.
100K+
Actions executed
70-88%
LLM cost reduction
7 levels
AIOps maturity model
3,000+
Pre-built action assists
150+
Tool integrations
RAOARA agents are meta-guiding agents. They don't execute autonomously. They build rich context in the Action Graph so the Voltron formation can execute with precision, not guesswork.
ActionBoard starts by understanding what you actually want, not just what you typed. The Recognize agent asks clarifying questions, resolves ambiguity, and locks in a precise goal before any resource is consumed. This is why 100% of AI execution fails at step one, and why we solve it first.
Execution mechanicGoal locked, formation activatedPhase 1 of 6
Each Lion agent has an immutable core. Users can extend with skills and rules, but cannot weaken the formation's safety constraints. Role integrity is what makes the formation work. When agents blur roles, coordination collapses.
Just as in the Voltron anime, the Lion does not move without a pilot. No agent executes without human approval. The formation drafts, proposes, and recommends. The human decides.
Planning, architecture decisions, execution sequencing. Final approval authority over all deployments. Black Lion leads the formation: nothing deploys without its sign-off.Immutable: Cannot delegate final approval authority
Knowledge retrieval, code context assembly, dependency mapping, semantic search. Green Lion ensures the formation operates on verified context, not hallucinated assumptions.Immutable: Cannot modify source documents
Code generation, feature implementation, testing, documentation. Blue Lion executes build tasks with full visibility into Green Lion's retrieved context and Black Lion's execution plan.Immutable: Cannot deploy directly to production
Security scanning, secret detection, vulnerability assessment, compliance checks. Yellow Lion blocks non-compliant actions before they reach the deployment stage, not after.Immutable: Cannot suppress security findings
Git operations, deployment execution, release management. Red Lion holds production authority, but only after Black, Yellow, and the human pilot have cleared the action.Immutable: Cannot self-direct without human approval
The formation-based cost model is not a marketing claim. It's a cloud engineering and performance game theory architecture. Five mechanisms work together.
Lions don't run simultaneously at full cost. Black Lion orchestrates a sequenced execution plan: only the Lion whose role matches the current task is active. Token burn follows the task, not a flat concurrent model.~30% reduction
Context is pre-assembled by Green Lion through the Action Graph before any generative call is made. TRM-tuned models receive pre-structured context rather than burning tokens on retrieval within the generation call.~25% reduction
Most operational tasks (classification, routing, compliance checking) are handled by small, domain-tuned models trained on your RAOARA traces. General-purpose LLMs are reserved for tasks requiring broad reasoning.~20% reduction
When the formation encounters an action type it has seen before, it auto-executes under the stored consent record: no re-confirmation call, no redundant context assembly. The consent ledger compounds efficiency with every use.~8% reduction
The Action Graph maintains both a hot layer (recent execution context) and a cold layer (crystallized long-term patterns). Retrieval costs drop dramatically because the hot layer handles 80% of queries at a fraction of cold-layer cost.~5% reduction
Advanced capabilities (multi-agent patterns, CAST configuration, domain SLM training) don't unlock on a billing date. They unlock when your execution history proves you're ready. The platform prevents you from skipping ahead, because skipping ahead breaks the formation.
20% AI Execution
You execute simple, well-defined tasks using pre-configured Lion agents. The platform guides you through RAOARA phases with explicit prompts. You build your first execution traces.
35% AI Execution
Goal complexity increases. You begin chaining actions across tools and building your own ActionLists. Green Lion's retrieval patterns start learning your most-used sources.
52% AI Execution
You unlock your first agentic execution patterns. The formation starts operating with less explicit guidance per step, your consent memory is deep enough to trust auto-execution on familiar action types.
66% AI Execution
Your execution patterns become a template for others. You can publish ActionList templates, delegate tasks to the Action Assist community, and customize Yellow Lion's compliance rules for your domain.
78% AI Execution
You design formation strategies for complex, long-horizon goals. Your RAOARA traces are generating high-quality contrast pairs. The system begins flagging you as eligible for SLM training data contribution.
90% AI Execution
You operate at the governance layer. You configure CAST steering vectors for your organization's compliance dimensions. Your crystallized knowledge base begins powering a domain-specific small language model.
97% AI Execution
You own a production small language model trained on your organization's execution history. You define formation patterns for other users. Your crystallized knowledge compounds across the entire organization.
ActionBoard's long-term memory (the Action Graph that captures your decision history, execution patterns, and crystallized knowledge) does not belong to us. It belongs to you. But private long-term memory requires you to take ownership of your chat traces.
Long-term memory saving
In encrypted storage
Generic AI tools harvest your interaction history to train their models. We do the opposite. Your RAOARA traces are your intellectual property. We can't learn from them without your explicit consent, and you can't benefit from long-term memory without actively claiming them as yours.
Every action type the formation executes for the first time requires explicit user permission. That consent is stored in a personal ledger: auditable, exportable, and revocable.
You claim your RAOARA traces through the Voltron Desktop Client. Unclaimed traces are ephemeral: they inform the current session but don't persist to long-term memory.
Once claimed, your traces build a private Action Graph: encrypted, stored in your designated persistence layer, and never used to train platform-wide models without explicit research consent.
Your private Action Graph makes subsequent RAOARA cycles faster, cheaper, and more accurate. The formation loads your context in milliseconds, not from scratch. This is the compounding advantage that grows with use.
At Level 5 AIOps maturity, your RAOARA execution history starts generating something more valuable than workflow automation: structured training data for a small language model tuned to your domain.
This capability requires earned AIOps maturity. It cannot be purchased or unlocked early.
Your 500+ verified execution traces, each one a structured record of goal, context, decisions, and outcomes, form the raw dataset. No manual labeling required.
Traces are automatically converted into matched compliant and non-compliant pairs. These pairs isolate exactly what makes an action correct: the signal CAST needs.
Conditional Activation Steering extracts behavior vectors from your contrast pairs. These vectors enforce your domain's governance at the model's internal activation level.
A small, domain-tuned model, trained on your actual execution history and not generic internet data, replaces general-purpose LLM calls for your core operational tasks.
Result: Expert-level performance in your domain at a fraction of general-purpose LLM cost, because the model was trained on how you actually work. Requires Level 5+.
The Action Graph is a directed acyclic graph (DAG) of everything the formation has done on your behalf: every goal clarified, every source queried, every action taken, every decision logged. It's what makes the Voltron formation coherent across long-horizon goals without requiring micro-consent for every step.
Industry deployments of the Voltron formation, each with its own ActionLists and compliance rules.
ActionBoard's Voltron formation is deployed in financial services environments with industry-specific ActionLists, pre-configured Yellow Lion compliance rules, and domain-tuned retrieval in Green Lion. The formation adapts to sector requirements. The architecture stays constant.
All tools are pre-configured and integrated into your ActionBoard workflow. No additional setup required.
ActionBoard meets you where you are. Your first goal clarification starts the formation. Your execution history builds the memory. The maturity follows. No credit card required. Your first 50 RAOARA cycles are free.