> ## Documentation Index
> Fetch the complete documentation index at: https://docs.manthan.systems/llms.txt
> Use this file to discover all available pages before exploring further.

# Traction and roadmap

\# Traction and Roadmap — Parmana

This document outlines current progress and the path to adoption for Parmana.

\---

\## Current state

Parmana is currently in the \*\*infrastructure definition and core system development phase\*\*.

The system architecture is fully defined:

AI → Signals → Governance → Authorization Decision → Execution Runtime → Attestation

Core components established:

\- Deterministic governance model

\- Signal validation layer

\- Authorization decision engine

\- Execution runtime enforcement layer

\- Cryptographic attestation system

\- Independent verification model

\---

\## What exists today

\### 1. Core architecture

\- Fully defined deterministic authority model

\- Separated intelligence, governance, and execution layers

\### 2. Documentation system

\- Architecture layer completed

\- Concepts layer completed

\- Whitepapers completed

\- Go-to-market narrative completed

\### 3. System design

\- Execution-bound authorization model

\- Replay protection model (`executionId`)

\- Cryptographic verification model (attestations)

\---

\## What is being built

\### Phase 1: Core enforcement runtime

\- Authorization Decision engine

\- Execution Runtime enforcement layer

\- Policy evaluation system

\### Phase 2: Verification layer

\- Independent verification tools

\- Attestation validation system

\- Audit reconstruction engine

\### Phase 3: Enterprise integration layer

\- API gateway enforcement mode

\- Sidecar / middleware deployment models

\- Workflow integration adapters

\---

\## Roadmap

\### Near term (0–3 months)

\- Stable execution runtime

\- End-to-end authorization pipeline

\- Deterministic policy evaluation engine

\---

\### Mid term (3–9 months)

\- Enterprise integrations

\- Audit dashboard system

\- External verification tooling

\- Production-grade deployment models

\---

\### Long term (9–18 months)

\- Full AI agent integration ecosystem

\- Runtime enforcement across distributed systems

\- Compliance-ready enterprise deployments

\- Category establishment: Authority Verification Infrastructure

\---

\## Adoption strategy

Parmana is designed to integrate into:

\- AI agent platforms

\- financial systems

\- enterprise automation stacks

\- infrastructure orchestration systems

It acts as a \*\*pre-execution enforcement layer\*\*.

\---

\## Why this will be adopted

Because organizations deploying AI systems need:

\- deterministic execution control

\- auditability of decisions

\- compliance guarantees

\- prevention of unauthorized actions

Parmana provides all four.

\---

\## Key insight

> AI adoption increases execution risk unless authority is explicitly enforced.

Parmana is the enforcement layer.

\---

\## Summary

Parmana is transitioning from:

\- system design → implementation → deployment layer

with a focus on:

> making AI execution safe, deterministic, and verifiable in real systems