Put AI in charge.Keep control.

Let AI make consequential decisions within your rules. Choose your models, keep your credentials out of their hands, and get evidence of the result.

Your models. Your rules. Your evidence.

More room to act.Less to leave to chance.

Delegate consequential decisions.

Review a payment, route a request, or prepare a system change. Define the permitted actions. Instantial enforces the boundary.

Keep choosing your models.

Use models for their intelligence without handing them the keys. Keep the decision rules with your workflow when providers change.

Get proof you can use.

Inspect evidence of the governed decision without retaining the personal data behind it. Give reviewers something concrete to examine.

One product for the decisions you want AI to take on. Start with the workflow you want to put to work.

Your work.Your rules.

Explore how Instantial governs decisions, keeps model choice in your hands, and produces evidence you can inspect.

What would you put AI in charge of?

Bring the work you want to delegate. We'll discuss the rules it needs, the systems it reaches, and how Instantial fits.

Get started

Confidence comeswith evidence.

  1. 01

    A decision you can inspect

    Open a worked example and its receipt. See what the evidence establishes and how to verify it.
  2. 02

    We asked them to break it.

    We hired an independent cryptography firm to try to break our system. They couldn’t. Full report available internally.
  3. 03

    A boundary rooted in hardware

    Hardware attestation gives you a basis for verifying the environment responsible for enforcing the rules.

See the workflow. Inspect the record. Ask the deployment questions that matter to your team.

Beyond guardrails.Compliance by design.

Your rules define what can become an output. Instantial enforces those conditions before release, without giving the model authority to negotiate them.

Swipe or scroll to compare all five approaches →

Feature comparison
What mattersAI workflow platformsProfessional applicationsGuardrailsChecks around AIObservabilityTraces & metricsLocal AIYour infrastructureInstantialGoverned outputs & release
Professional workflow applicationsYesNoNoNoYes
Configurable policy checksVariesYesNoNoYes
Operational traces & metricsVariesVariesYesVariesYes
Deploy on your infrastructureVariesVariesVariesYesYes
Rules independent of model providerVariesVariesNoNoYes
Hardware-attested authority boundaryVariesNoNoVariesYes
Decision proof without personal-data retentionVariesNoNoNoYes
Custody evidence required before releaseVariesVariesNoNoYes
  • Yes
  • No
  • Varies
Get started

Examples: Harvey’s professional applications · OpenTelemetry’s observability concepts · NVIDIA’s guardrail types · Ollama’s local and cloud data handling

Your models.Your infrastructure.Your authority.

Start with one workflow. We'll map the permitted actions, the systems it reaches, and the evidence your team needs.

Get started
  1. 1Connect

    Identify the systems, credentials and operating rules involved in your workflow.

  2. 2Evaluate

    Review the product, integration requirements and applicable evaluation evidence.

  3. 3Put it to work

    Agree the deployment scope, responsibilities and commercial terms for your environment.

Built by people who haverun systems under pressure.

Machine learning, enterprise products, and a decade of responding to failures at platform scale.

  • KB

    Kollin Brandenburg

    Founder

    Software engineering manager who has led teams building payments and financial software at global scale. Previously at Visa and Finastra, shipping systems where reliability, security, and regulatory scrutiny come with the job.

  • AO

    Andrew Overby

    Founder

    Product and operations leader across ERP, payments, and compliance at ServiceTrade and Community Brands. Grew product recurring revenue 76% and cut churn in half. Previously at Coinbase. NYU.

  • KG

    Katie Grover-Bennett

    Founder

    Designed the Instantial architecture, authored its specification, and builds the Rust enforcement kernel. Built incident-management systems from zero at YouTube and Facebook, with a decade of platform-integrity work across Google, Meta, and Coinbase. Ten architecture patent applications filed through Foley Hoag. Dartmouth · Baylor · St Andrews.

Advisors & collaborators

  • Scott Cunningham

    Head of research, causal inference · Harvard / Baylor

  • Daniel Bliss

    Hardware co-architect, silicon and attestation · ASU

  • Laura Schulz

    MIT cognitive science

Different reasons.The same possibility.

  • Privacy
  • Receipts
  • Independence
  • Peace of mind
  • Control
  • CYA
  • Confidence
  • Accountability
  • Superpowers
  • Trust
  • Security
  • Proof
  • Compliance
  • Transparency
  • Your data
  • Sovereignty
  • Reliability
  • Better decisions

Before youget started.

What would you putAI in charge of?

Get started

Our Mission

Experts on Where “Good Enough” Breaks

In our combined decades of experience we have learned the quiet danger of breaking points: of distributed systems, of policies, of technology itself. Things that worked before don’t work now. Things that worked in a sandbox are laughably insufficient at hyperscale. Things that seemed impossible a decade ago are now recent history.

The places where good enough breaks? That’s where catastrophic failure waits.

We are the operators who have kept “good enough” going for our whole careers. The countless operational and technical fractures that teams at large enterprises seamlessly repair don’t disappear. They accumulate risk over time. The folks working tirelessly on the inside know the secret fragility of the very enterprises that are setting the standards for what safety means, what security means, and what acceptable privacy standards look like. It isn’t enough.

AI + Humanity

Tech has changed our daily life in the past fifteen years. We have embedded systems in almost everything we do that actively impact our ability to be productive, to travel, to socialize, to make or spend money… no part of life seems untouched. And, hey, we love tech.

But GenAI and whatever comes next are raising the stakes. The potential for good is huge. The potential dangers seem exponentially higher.

The acceptable risk of yesterday is becoming increasingly unacceptable. We believe that privacy standards need to become architectural guarantees instead of corporate regulatory risk. We believe that safety means knowing any machine element follows policies 100% of the time and human elements are held accountable. We believe that security means a chain of trust that is clear on its boundaries for every user in every deployment.

Building a Better Future

We are optimists. We are all passionate about the advancement of the frontier. We believe that the success of innovation is, or should be, everyone’s success.

Toward that end we are not building Instantial to slow down the future. Instead, at its core, our company is part of enabling the acceleration of that future. We believe efficiency, advanced capability, and unmatched performance are byproducts of appropriate restraint. Innovation is not linear and we are not here to be incremental. We are building toward the next leap.