What we can build with Meta Llama
ShooflyAI builds on Meta Llama when a client wants an open-weight model they can self-host for privacy, cost control, and full ownership of the model itself, with no per-token fees or data leaving their environment.
These are example builds, not client case studies. We scope the real build to your stack and put an ROI estimate on it in an Operating Assessment first.
With Meta Llama you can build AI agents that run on infrastructure you control, which matters when privacy, data residency, predictable cost, and full ownership are the priority. Because Llama is open-weight, the model can run on your own cloud or hardware with no per-token fees and no data leaving your network, useful for high-volume classification, extraction, and private document work, with people approving judgment calls. Llama is a building block, the model itself, not a finished business agent. ShooflyAI turns it into a custom agent scoped to your stack and processes, sized to your hardware, with human review where it counts. You own the code, the deployed weights, prompts, data, and IP outright, with no revenue share and no lock-in to us.
10 ways to use Meta Llama with AI agents
- Self-host for full data privacyThe agent runs on infrastructure you control so sensitive data never leaves your environment.
- Process high volume cost-effectivelyIt handles large workloads on owned infrastructure with predictable cost instead of per-call pricing.
- Run offline or air-gappedThe agent operates without external API calls where connectivity or security rules require it.
- Classify documents at scaleIt categorizes large batches of internal documents inside your own environment.
- Power an on-premise assistantThe agent answers staff questions from your data without sending anything to a third party.
- Fine-tune on your domainIt can be tuned on your own examples so outputs fit your terminology and workflows.
- Extract structured data privatelyThe agent pulls fields from sensitive documents entirely within your infrastructure.
- Avoid vendor lock-inIt runs on an open model you control, so you are not dependent on one provider's pricing or terms.
- Redact and process PII in placeThe agent handles personal data without it ever leaving your controlled environment.
- Embed into owned productsIt ships inside your software with the model deployment fully under your control.
Using Meta Llama on its own vs. a custom ShooflyAI agent
| Dimension | Meta Llama open-weight models (a self-hostable model, not a turnkey business agent) | Custom ShooflyAI agent |
|---|---|---|
| Setup | You host the model and build everything around it | We deploy and build a finished agent for you |
| Handles your multi-step workflows | Raw model; all workflow logic is yours to build | Built to run your specific multi-step processes |
| Works across your other systems | No integrations included; you build each one | Connected to your systems and data for you |
| Who owns and maintains it | You own the open weights and your build | You own code, weights, and IP; we can maintain |
| Cost model | Your own compute and hosting, no token fees | Project build plus your self-hosted infrastructure |
Frequently asked questions
Why use Llama instead of a hosted frontier model?
Llama is open, so it can run on infrastructure you control. That gives you privacy, predictable cost, and independence from a single vendor, which matters for sensitive or high-volume workloads.
Can a Llama agent run on our own servers?
Yes. Llama can be self-hosted on your cloud or hardware, so data stays inside your environment and the agent does not depend on an external API.
Do we own a Llama agent ShooflyAI builds?
Yes. You own the agent code, prompts, workflow logic, and data, and you control the model deployment itself rather than renting access to it.
Is Llama private enough for sensitive data?
Because it can run in your own environment, data does not have to leave your control. ShooflyAI configures the deployment to your security and compliance requirements.
How does Llama help with cost at scale?
Self-hosting an open model can make high-volume workloads more predictable than per-call API pricing. ShooflyAI helps size the deployment to your usage and budget.
Want to see what we would build for you?
We start with an Operating Assessment that maps your highest-value workflows and puts a hard ROI estimate on them before any build. You own the code, the data, and the IP.
Get your Operating Assessment →