Augment vs Personal AI

Augment turns expert business processes into automated workflows for sales teams and financial institutions. Instead of adding another dashboard, it delivers finished work products like pre-meeting briefs, CRM updates, and covenant exception reports directly into the inbox, Slack, and CRM records your team already uses. Every consequential step stops at a named human gate before anything closes.

Horizontal AI copilots summarize meetings or draft emails, but they sit beside broken workflows rather than fixing them. Augment redesigns the process first, then runs it through three layers: a data plane that connects to existing systems without copying data, a control plane with explicit human gates, and an intelligence layer encoding your policies and thresholds. McKinsey data cited on the site shows workflow redesign was the single largest predictor of AI P&L impact, which is why Augment targets the work between systems rather than replacing them.

Revenue teams get momentum briefs before every call and executive pulses every Monday. Banks and funds get 44 pre-built agent teams for covenant monitoring, investor onboarding, and credit file assembly. OneVizion's CEO reports that handoffs that used to take days now happen in seconds.

Personal AI builds memory infrastructure that gives AI a persistent identity instead of resetting every session. Its Memory Core encodes, stabilizes, stores, retrieves, and updates experiences so an assistant remembers what it has lived, not just documents you upload. The stack spans My AI for end users, Persona Studio for builders, and carrier-grade Memory Core deployments on operator networks.

Most AI assistants treat context as static files you attach before each chat. Personal AI separates memory (accumulated experiences with temporal structure) from context (static uploads) and lets identity emerge over time. Carrier benchmarks on Comcast's network cite 15ms time to first token, $0.02 per million tokens, and sub-500ms end-to-end voice versus cloud LLM baselines.

Telecom carriers, enterprise AI teams, and individual users who want a long-running assistant use Personal AI. Carriers deploy MODEL-4 on their own networks under custom agreements. Builders use Persona Studio to configure personas without code. Consumers get My AI, an assistant that remembers conversations and learns preferences over time.