SmartOps AI: Autonomous Support & Operations Agent

I’m building SmartOps AI: an end-to-end autonomous agent that sits inside our support workflow, understands every incoming request, takes action on its own, and only taps a human when it is unsure. The core of the system will be a fine-tuned large-language model for reasoning and response generation, backed by a separate intent-classification model that produces a clear confidence score. Whenever that score falls below a threshold, the agent must automatically hand the case to one of our human agents.

Integration focus
Right now the agent only needs to plug into our customer-support stack, specifically Salesforce Service Cloud. Through the native APIs it must be able to update customer records in real time and, when required, raise an explicit escalation ticket for a human. In the future we may expand into internal IT automations or database queries, so designing clean, extensible tool-calling logic is important.

Scope you’ll own
• Agent runtime that can loop through decisions, call external tools, and log every step.
• Fine-tuning pipeline (data prep, training, evaluation, deployment) for the LLM.
• Stand-alone intent/classification model wired into the runtime for confidence scoring.
• Admin dashboard that lets me monitor conversations, review actions, tweak thresholds, and roll back changes instantly.

Acceptance criteria
1. A live demo showing the agent updating a Salesforce record and, on low confidence, escalating to a human queue.
2. Unit and integration tests covering tool calls and confidence-based branching.
3. Clear deployment scripts (Docker or similar) so we can host the stack on our own cloud.
4. Concise documentation for future contributors.

If you’ve shipped production-grade AI agents, have rock-solid API skills with Salesforce, and can move from model training to frontend dashboards without hand-holding, I’d love to see your approach and timeline.