SmartDigitalMinds

Local AI product

A private AI agent for the work that happens every day.

SmartDigitalMinds packages a local agent runtime, approved hardware, and business integrations into one managed assistant for communications, documents, schedules, and project follow-up.

Plan a local agent View hardware profiles
Compact local AI workstation connected to a business dashboard

Hardware profiles

Local models close to the team, the data, and the workflow.

The product can be designed around compact local AI hardware, from Ryzen AI Max+ 395 systems for efficient team assistance to NVIDIA DGX Spark-class GPU systems for larger local model workloads. Model size depends on memory, quantization, context length, and workload, with DGX Spark-class profiles targeting up to 200B-parameter local model inference.

GPU local

NVIDIA DGX Spark-class

For teams that need larger local models, stronger GPU acceleration, and private agent workloads near the desk.

Edge local

Ryzen AI Max+ 395

For compact AI PCs and workstation-class assistants handling daily communications, files, and project activity.

Managed runtime

Local agent stack

Model serving, memory, connectors, monitoring, and operating rules configured for the business process.

Daily task support

One local assistant across messages, documents, meetings, and follow-up.

The agent supports the repeated work that usually spreads across chats, inboxes, documents, calendars, spreadsheets, task boards, and meeting notes.

  • CommunicationsAssist with WhatsApp, Telegram, Signal, Teams, and internal handoff workflows.
  • Email and office suitesDraft replies, summarize threads, prepare documents, update sheets, and organize follow-up.
  • Project managementTurn updates into tasks, reminders, status summaries, blockers, and weekly management views.
Local AI agent connected to communication, document, calendar, and task workflows

Delivery model

Built like an operating layer, not a demo box.

  1. 01

    Scope

    Choose the daily workflows, data boundaries, users, escalation rules, and required integrations.

  2. 02

    Install

    Provision the local runtime, model profile, memory service, connectors, and controlled access paths.

  3. 03

    Train the workflow

    Configure prompts, tool permissions, retrieval sources, reporting cadence, and acceptance checks.

  4. 04

    Run and improve

    Monitor outcomes, refine behavior, close gaps, and expand only when the workflow proves useful.

Next step

Start with the daily work the team already repeats.

agents@smartdigitalminds.com

Send the workflows, current tools, data constraints, and whether the preference is DGX Spark-class GPU hardware or Ryzen AI Max+ 395 local AI PCs.