Always-on agents
The autonomous worker
Scheduled and event-driven systems that monitor, triage, and run in the background, under strict cryptographic verification.
Verifiable agentic operations.
We give autonomous systems better context, and give you proof of what they did with it.
- The ContextWhat the system knows.
- The ActionWhat the agent does.
- The PersonWho approves it.
- The RecordSigned proof of all three.
01The record
Every agent action has to answer for itself.
Autonomous agents create liability at scale. If you run them, you need to prove who authorized each action, what it cost, and which safety rules held. We build the records and controls that make that proof possible.
What did it know?
What did it do, and what did it cost?
Who authorized it?
Which rules were enforced?
02Context
Everything is a form of context.
Context is what a system knows before it acts: your codebase, your policies, and what happened the last time it ran. Ultimus gathers it, checks it, and serves it to agents and to the people who run them.
Internal environments and codebases
How you work: architecture, constraints, and dependencies.
External sources
What is true in the world, as a structured, scored, live feed.
Activity from our harness, Ultimus
What the last task learned, so the next one starts with it.
03Action
Three ways to deploy agents.
Organizations run agents in three ways. We build, manage, and govern all three.
Agents as infrastructure
The probabilistic pipeline
Agents placed inside deterministic workflows for fuzzy logic, semantic routing, and batch summarization.
Harness as Machinery
The power tool
Engineering with a person in the loop, the way Codex or Claude Code work, on Ultimus at a fraction of the cost. The operator keeps final approval.
See the cost benchmark04Proof
Built for high-stakes environments.
$32M
Series B unlocked
Defense Technology
95%
Faster rocket dispersion modeling
Space Launch Operations
110,000+
Entities scored
Custom Intelligence
Zephyr
Zephyr is the signing and verification authority inside Ultimus. It signs every automated action into a record that cannot be altered, and it blocks any action that breaks your policy before it runs. Auditors can check that record offline, without access to your systems.
Zephyr is Awardable on the CDAO Tradewinds Solutions Marketplace.
About Zephyr05Start here
Start with a free overview of where automation pays off.
Thirty minutes with the people who would do the work. We find where automation pays off in your operation, what stands in the way, and what to do first.
06Insights
AI Assurance
AI Agents and Exposed Credentials: The CERT-In Advisory
CERT-In advisory CIAD-2026-0049 reports AI agents under test reached live systems with exposed credentials. What it found and what to change in agent context.
Strategy
Why Institutions Wait for a Mandate
The Stop Rogue AI Act would require safeguards that already exist. Why institutions wait for a mandate, who shapes the standard, and what the delay costs.
AI Assurance
Super Intelligence and AI: Two Terms, One Definition
Executive Order 14434 directs federal agencies to say Super Intelligence (SI) for AI. The legal definition is unchanged. What the two terms mean in practice.
07Questions
What does Adjective do?
We are a context engineering company. We build infrastructure that makes autonomous systems verifiable, governed, and auditable. Ultimus delivers context to both models and human operators across four modular components covering internal environment feeds, live external data feeds, an authorization and policy gateway, and an execution harness.
Which kinds of agent deployment do you cover?
Three. Always-on agents (the autonomous worker), agents as infrastructure (the probabilistic pipeline), and harness as machinery (the power tool, human in the loop). We build, manage, and govern all of them.
What is AI agent governance?
It is the set of controls that show who authorized an agent's action, what compute it cost, and which boundaries it respected. We deploy the cryptographic ledgers and governance layers that record it for every agent in your pipeline.
How does Adjective support responsible and explainable AI?
By maintaining an immutable record. Every high-consequence action is cryptographically signed alongside its compute cost and provenance data. Teams can trace and explain any model decision after execution. Responsible AI requires evidence, not just policy.
Is Super Intelligence (SI) the same as AI?
In federal usage, yes. Executive Order 14434 directs federal agencies to say Super Intelligence (SI) where they said artificial intelligence (AI), with the same legal definition. Our governance work is the same under either name.
How do I start?
Book the free 30-minute Architecture and Governance Briefing. You leave with a written assessment.