Exhibit № 06 — 2025 — 2026
Autonomous Systems
Software that runs the business.
An internal fleet of autonomous agents: 17 agents running marketing, sales, support and billing with human-in-the-loop approvals; an AI engineer that ships pull requests; trading bots executing on live markets.
Agent fleet · 17 active
✓ prime-agi · opened PR #214 — fix invoice rounding
→ tests passed (34/34) · awaiting human review
→ cost today: $0.41 / cap $5.00
MediumPython · FastAPI · Celery · Redis · Claude · GPT · open-weight models · Azure AI Foundry · Terraform
FormatDashboards · APIs · Live markets · Azure cloud
StatusInternal fleet, in operation
The thesis
The best way to sell AI automation is to run on it. Prime Labs builds autonomous systems for itself first — a company that markets, sells, supports and operates with agents — and brings clients the patterns that survived contact with reality.
The fleet
Seventeen agents cover the business surface: marketing and social publishing, sales outreach, support triage, onboarding, churn watch, reputation monitoring, billing and dunning, competitor intelligence, QA. Critical actions queue for human approval in a live dashboard. A multi-provider model layer routes each task by cost tier across Claude, GPT, Mistral, Llama and DeepSeek — the whole fleet runs on roughly $15 of LLM spend a month.
The engineer
prime-agi is an autonomous software engineer: scoped to a client, project and environment, it investigates services, edits code, runs tests and opens pull requests — with tier-gated permissions, an append-only audit log, daily cost caps, and a hard rule that it never merges or deploys itself. Work arrives from Jira, Linear, Azure DevOps and email.
The markets
Three generations of quantitative trading systems execute on live prediction markets — probability models over streaming exchange data, fractional Kelly position sizing, drawdown circuit-breakers and kill switches. No LLM in the hot path: statistics, discipline and risk management.
In the frame
What it does
A 17-agent fleet
Marketing, sales, support, onboarding, churn watch, billing — the business surface, run by agents on ~$15/month of LLM spend.
Humans gate what matters
Critical actions queue for approval in a live dashboard; everything else runs on schedule, 25 tasks deep.
An engineer that ships
prime-agi investigates, edits, tests and opens pull requests — tier-gated, audit-logged, never merging its own work.
Discipline on live markets
Probability models, Kelly sizing, drawdown circuit-breakers and kill switches — statistics in the hot path, not vibes.
The scope
What we delivered
- 01Marketing, sales and support agents that draft, schedule, reply and follow up
- 02An approval queue — anything critical waits for a human decision
- 03An AI engineer that investigates issues, fixes them and proposes the change for review
- 04Trading systems with strict risk limits and automatic kill switches
- 05Dashboards showing every action taken and every cent spent
17
agents on the clock
24/7
the fleet never sleeps
100%
of critical actions human-approved
~$15
a month to run it all
Next exhibit
Kansa