model strategy
The model stack behind every private deployment
Your private AI environment ships with a curated trio of foundation models so every workflow is covered. We balance latency, reasoning ability, and parameter count to keep quality high without overspending on compute.
Primary models included
Llama 3.1 70B
Enterprise reasoning workhorse for long-form answers, structured plans, and high stakes decision support.
- Context window: 128k tokens
- Best for: policies, summaries, draft generation
Mistral 7B
Lightning fast assistant for chatty interactions, form filling, and routing logic where speed is vital.
- Context window: 32k tokens
- Best for: quick replies, automations, fallback logic
Qwen 2.5 14B
Specialized model tuned for technical content, multilingual responses, and structured data extraction.
- Context window: 64k tokens
- Best for: spreadsheets, code, financial memos
Selecting the right model for each task
During onboarding we map your workflows to the appropriate model tier. The orchestration layer automatically routes calls so agents and end users see consistent performance.
| Scenario | Recommended model |
|---|---|
| Executive briefings and long reports | Llama 3.1 70B |
| Slack or Teams agent responders | Mistral 7B |
| Spreadsheet cleanup and analytics | Qwen 2.5 14B |
| Multi-step automations | Mistral 7B with tool calling |
| Legal or medical policy memos | Llama 3.1 70B + retrieval |
Routing intelligence
- Usage telemetry helps us rebalance workloads between models without touching your applications.
- Fallback policies redirect to a secondary model if latency spikes or a service is unavailable.
- Guardrails enforce token, cost, and compliance limits per team or integration.
Prefer another OSS checkpoint? Bring your weights. We validate performance and update routing rules accordingly.
Fine-tuning and extensions
Domain adapters
LoRA adapters capture your vocabulary, templates, and tone without retraining the entire model.
Retrieval augmented generation
We plug structured knowledge bases into the prompt so answers stay grounded in your source of truth.
Safety tuning
Custom moderation rules and refusal behaviors align with your compliance policies and brand voice.
Evaluation harness
Automated benchmarks track accuracy, latency, and cost across releases so upgrades are data driven.
Explore the model roadmap with us
We share quarterly guidance on emerging checkpoints, parameter trade-offs, and licensing changes so you can plan ahead.
Book a model strategy sessionCommon questions
Can we swap in proprietary models?
Yes. We integrate with Azure OpenAI, Anthropic, or Gemini while keeping routing logic consistent.
Do you support vision or multimodal models?
We deploy multimodal variants on demand, including image understanding pipelines for field teams.
How are weights stored?
Artifacts stay inside your object storage buckets with lifecycle policies and restricted access groups.