Keep your data safe while using whichever LLMs are right for you

Your organization's data (including employee information, client records, proprietary workflows, and intellectual property) deserves protection…whether it lives in a file cabinet, behind a VPN, or within an AI tool. The latter is where Swept supports you. We ensure that your data is protected within your AI tools of choice, while allowing your team access to any LLM or combination you prefer.

There's an assumption embedded in most enterprise AI rollouts that accessing powerful models means accepting data risk, that sensitive client information will pass through an infrastructure you don't own or control. It doesn't have to be that way. You probably know that you don't want your data training someone else's model, but true security requires more than just turning that toggle off or choosing between an open-weight or closed-source model.

A rigorous implementation can give your team access to any model and any tool while keeping your data (and, by extension, your clients' data), within the confines of your organization.

What We Protect

(just a sampling)

Your organization's data

Proprietary workflows, internal documents, and strategic information will not leave your environment or contribute to a third-party model's training data.

Your employees' data

Personal information, communications, and usage patterns stay within access controls mapped to your org structure. Who can see what is defined by you.

Your clients' data

In regulated industries such as insurance, client data carries legal and fiduciary obligations. Swept enforces the boundaries that make sure your AI usage never puts client confidentiality at risk.

Your intellectual property

The way your organization works, such as your underwriting logic, your claims processes, and your accumulated institutional knowledge, is a competitive asset. It doesn't belong in a shared model.

What We Build

A contained environment for every model you use

Swept builds an environment where your team's interactions with any LLM, whether that's Claude, GPT, Gemini, or others, stay within a governed perimeter. Data sovereignty and encryption are in place before the first prompt is sent. Absolutely nothing leaves without your authorization.

Access to any model, on your terms

Model-agnostic access means your team isn't locked into a single vendor or a short approved list. Swept supports deployment across leading LLMs and can integrate nearly any combination of your existing vendor relationships into a single governed environment. Before any model goes live, we test it against your actual data and workflows so that your selection is based on your evidence, not vendor claims.

When the task changes, the model can too. Moving a user, team, or workflow to a different model takes a single click, helpful because the right model for one task isn't always the right model for the next. Cost savings follow naturally from identifying these best-fit cases, but a switch is primarily recommended due to a workflow match.

Access controls that reflect your org structure

Role-based permissions, AD-integrated user management, and per-user controls ensure that the right people have access to the right tools. Access controls aren't applied generically; instead, they're mapped to how your organization actually works.

Hands-on setup with a named engineer

Swept assigns an engineer who knows your systems, your team, and your goals. Initial configuration, integration, and rollout support are part of the engagement. Your team doesn't inherit a system they don't understand; instead, we help them build their capability alongside ours.

The Steps We Take

  1. 01

    We evaluate

    Before any model touches your data, we test candidate models against your actual workflows. You see accuracy, reliability, and cost tradeoffs clearly…under real conditions (yours!), not controlled demos. We have no vested interest in which AI tools you select.

  2. 02

    We configure

    Data sovereignty controls, encryption, role-based access, and audit logging are established before your environment goes live. Every data handling rule is in place before anyone sends the first prompt.

  3. 03

    We connect

    We build the integration layer that connects your chosen models to your existing systems complete with data classification rules and authentication enforced at every connection point.

  4. 04

    We roll out

    Swept manages the rollout alongside your team so that paired working sessions build your team's confidence as each project ships. The goal is to transfer autonomy, not build unnecessary dependence on us.

What You Get

  • A governed environment where your data stays yours
  • Model-agnostic access: any LLM, within your data boundaries
  • Protection for company data, employee data, client data, and intellectual property
  • Encryption and data sovereignty controls established before go-live
  • Continuous monitoring of data movement across every model in use
  • Pre-deployment model evaluation on your actual data and workflows
  • One-click model switching: the right model for each task
  • AD-integrated user management and role-based permissions
  • A named engineer accountable to your project scope
  • Department-by-department rollout with training that transfers

FAQs

Does our data train the models we use through Swept?
No. Your data does not contribute to third-party model training. What moves through your environment stays in your environment.
Which models can we access?
Swept supports deployment across all leading LLMs. Your model selection is based on your particular use cases and is confirmed during an evaluation phase.
How are access controls configured?
Access controls are mapped to your existing organization structure and integrated with your directory (AD or equivalent). Role-based permissions are established during configuration, before rollout begins, and are editable only by approved users.
How long does setup take?
The foundation typically runs 16–20 weeks end-to-end. Some projects can begin as early as week 3, depending on data sensitivity and scope.
What happens after setup?
Swept shifts to an advisory capacity while your team owns the environment. Quarterly governance reviews and on-call technical support keep things running as you expand.