Technology
Llama
Llama implementation for production software delivery with clean architecture, maintainability, and predictable rollout.
Best For
Ideal use cases
Teams needing more control over model hosting and data boundaries
Products with private/VPC deployment requirements
Workflows that benefit from open-source model flexibility
What We Build
Projects we deliver
Self-hosted LLM inference services
Private assistants and copilots with governed access
RAG stacks paired with private model deployments
Ecosystem
Compatible tools & integrations
Seamless Integrations
Works with your existing stack
Use Cases
Recommended use cases
Enterprise AI in restricted environments
Private knowledge assistants with strict access control
Cost-optimised long-running AI workloads
Delivery
How we deliver
We plan deployment around latency, throughput, and infra constraints.
Safety controls and evals are added to keep behavior stable as you iterate.
We document operations so your team can run and scale the system.
FAQ
Frequently asked questions
Yes. We can deploy in VPC/on-prem environments with monitoring, access controls, and operational runbooks.
Sometimes. Costs shift from API spend to infrastructure. We help evaluate the trade-offs for your usage patterns.
Yes. We pair private model deployments with retrieval pipelines and citations for grounded answers.
AI
Add AI on top of this stack
Two common AI services that pair well with this technology, plus a fixed-scope gig to start quickly.
Related
Explore related technologies
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