@agent-name
.👉 Tip: Agents encapsulate LLM calls plus API connections and business logic, giving more power than a single chatbot.
✓ Start small – prototype with one agent, then chain more.
✓ Reuse Novus Originals before building from scratch.
✓ Maintain data control – work on Cloud, On-Premise, or Hybrid environment.
👉 Tip: Dot “advises RAG, agent, orchestration, workflow” customization first; fine-tuning is only suggested if these do not reach the desired outcome.
Choose model fine-tuning only if the above steps cannot hit required accuracy, brand tone, or compliance thresholds.
👉 Tip: All fine-tuning can be performed on open-source models and still deployed on-premise, so your data never leaves your environment.
✓ Start with RAG and agents — quicker and more cost-efficient.
✓ Use LoRA when hardware is limited or you need quick iterations.
✓ Apply DPO/PPO/RL only for advanced alignment needs.
✓ Keep experiments isolated by using New Chat for each test run.
✓ Monitor token usage in Dot’s built-in tracking to stay on budget.
✓ Maintain data control with on-prem or hybrid deployment.