LimitifyAI infrastructure that is governed by design, not by promise.
One shared registry. One permission gateway. One learning loop. Every agent we deploy is auditable, bounded, and measurably better than it was last month — because the governance was built before the agents were.
- Registry-enforced scope
- Fail-closed permission checks
- Append-only audit logs
- Per-agent credential isolation
- Human-gated production writes
- Structured learning loop
- Per-IP rate limiting
- Four-tier document visibility
Matter AI — one engine, many matters.
One shared engine hosts many independent matters — each with its own knowledge folder, system prompt, user whitelist, and escalation path. Public matters serve open portals; private matters gate access with OTP and a server-side whitelist. Live today powering the acquisition-partner recruitment portal for SmartifyTrade.
Four structural guarantees, applied to every agent we build.
Not policy documents — runtime checks. If an agent action would break one of these, it does not execute, and the attempt is logged for review.
Permission Gateway
Every agent action passes a central permission check before it executes. An agent cannot act outside its declared scope — the attempt fails closed and is logged.
Agent Registry
Every agent is registered with its category, host, permissions, and the client it is deployed for. Nothing runs unregistered, and nothing runs unattributed.
Self-Learning Loop
Log · Rate · Bug · Improve. Every run is logged, scored, and fed into a structured improvement cycle that a human reviews before anything changes.
Human-Gated Control
Category A and B agents act within explicit permissions. Category C and D agents never write to production or contact a user directly — a human clears it first.
The S5 Principle
The standard that governs every agent we build, regardless of client or use case.
Fails closed. Refuses ambiguous input rather than guessing.
Every credential separated, every action logged.
Horizontal by design, with per-agent isolation.
One agent, one job — no shared blast radius.
Learns from every run. Discipline, not drift.
A growing set of agents, each with a defined job.
11 live in production, 3 in active development. Every one carries the same registry entry, the same permission gateway, and the same learning loop.
FPA — Founder Personal Agent
Master control agent — interprets founder intent, analyzes risk/impact, coordinates execution across every other agent.
Kuku — Public Chatbot
Public-facing support agent live on SmartifyTrade (Client #1) — handles student, educator, and guest queries in English, Hindi, and Hinglish with automatic language detection.
FOPS — External Ops Agent
Handles external operations for the founder — marketing drafts, outreach, file and folder management — with zero access to core production systems, by design.
Aakruti — Master Scanner
Second-tier problem solver. Classifies incoming technical reports and support tickets, drafts responses for human review, and scans operational logs for anomalies.
EAS — Educator Application Scanner
Screens educator applications on SmartifyTrade against platform data and policy rules, producing a structured scan report for a human reviewer.
Educator Co-Pilot — Readiness Scan
Public, rate-limited lead-generation tool — analyzes a creator’s public content library and returns a readiness score, findings, and curriculum-gap suggestions.
SmartifyTrade runs on Limitify AI agents today.
A trading-education platform in production — its public support, application screening, operational monitoring, outreach intelligence, and multi-matter portals all run on agents built and governed by Limitify AI. Same architecture, same registry, same learning loop this site describes.
Building the infrastructure layer,
one governed agent at a time.
For enterprise inquiries, partnership discussions, or technical due diligence — reach out directly and we will walk you through the registry, the gateway, and the logs.