Artificial intelligence is rapidly becoming part of every business process. What began as isolated experiments with chatbots and coding assistants is evolving into a distributed ecosystem of AI agents, reasoning models, MCP servers, knowledge bases, and autonomous workflows.
As adoption accelerates, organizations face a new challenge.
How do you govern different models across multiple vendors ? How do you control costs ? How do you protect sensitive information ? How do you prevent AI agents from performing unsafe actions ? And How do you provide every model with trusted organizational knowledge without sacrificing security or creating vendor lock-in ?
These are infrastructure problems Chrysent was created to solve.
Chrysent is building an enterprise AI control plane that provides a single layer of governance, security, compliance and operational intelligence across an organization's entire AI ecosystem.
Rather than replacing existing AI providers or development tools, Chrysent sits between users, applications, AI models, enterprise knowledge, and execution environments, creating a unified operating layer for secure AI adoption.
The platform enables organizations to:
- Govern AI usage across multiple model providers
- Enforce consistent security and compliance policies
- Protect execution environments from unsafe AI actions
- Reduce operational costs thru visibility and optimization
- Make institutional knowledge securely accessible to AI systems
- Audit every interaction with complete traceability
- Prepare for large-scale autonomous software delivery
The result is an infrastructure layer that allows organizations to adopt AI with the same operational discipline they already expect from cloud platforms, identity systems, and security infrastructure.
The Chrysent platform is composed of seven products that can operate independently or togetheras a unified architecture.
The operational backbone of the platform.
AI Gateway centralize model access across providers while delivering governance, routing, budgeting, analytics, policy enforcement, immutable audit history and full AI session replay.
It provides organizations with a consistent operational view regardless of which LLMs or AI vendors are being used.
Secure execution for AI Agents.
As AI systems increasingly invoke tools, interact with operating systems, access remote infrastructure and comunicate with MCP servers, execution security becomes critical.
Bastion establishes controlled execution boundaries that allow usefull automation while preventing unauthorized or dangerous actions before they occur.
The Bastion system has a fully customizable policy engine that supports multiple defense layers, from simple regex matching to purpose built classification models.
Trust and security for every AI interaction.
The Touchstone continuously evaluate user input prompts and model outputs to detect prompt injections, jailbreak attempts, unsafe outputs, sensitive information exposure and policy violations.
It provides real-time safeguards before requests reach the models and before responses reach users or downstream systems.
It shares the same customizable policy engine with the Bastion, and it supports redaction of private identifying information, it can block and report unsafe or illegal AI usage.
AI-native understanding of software source code.
Axis Code transforms repositories into semantic knowledge graphs that AI systems can navigate efficiently when building new features in large code bases.
Developers gain contextual code search, dependency analysis and significantly more efficient AI-assisted software development through a retrieval system that minimizes unnecessary context and reduces token consumption.
This system increase speed during the discovery phase of AI agent development of new product features in pre-existing code bases. It supports more than 300 coding languages.
Governed organizational memory.
Institutional Knowledge is transformed into a secure retrieval layer that serves both humans and AI agents.
Rather than duplicating documentation across prompts, and tools, organizations establish a single governed source of contextual truth with policy aware access controls.
Axis Knowledge Base index of sources of knowledge in your enterprise: internal wiki systems, software development lifecycle artifacts, incident reports, enterprise document repositories. It aggregates them and make it available thru full text search, semantic search and knowledge graph to AI Agents.
Long-Horizon AI investigation and research.
Deep research combines resoning models, web research, organizational knowledge, and software context into structured research workflows capable of producing transparent, auditable analyses suitable for enterprise environments.
Every single claim is backed by evidence, with an actual source.
Structured software delivery with AI agents.
OPI Forge is Chrysent's coding harness for agent-assisted software engineering. It organizes work around specifications, implementation steps, review, testing, and audit trails so teams can use AI agents without losing control of the delivery process.
OPI keeps humans in charge of direction and approval while giving agents a clear workflow for making and validating changes. The goal is straightforward: help teams deliver software faster while preserving reviewability, security boundaries, and operational discipline.
Each Chrysent product delivers value independently.
Together, they form a cohesive AI operating platform.
At the center, the AI Gateway control every interaction.
Touchstone secures conversations.
Bastion secures execution.
Axis Code and Axis Knowledge base provide trusted and efficient context.
Deep Research orchestrates complex investigative workflows.
OPI Forge extends these capabilities into the software development lifecycle.
This layered architecture allows organizations to adopt AI incrementally while maintaining consistent governance across every stage of the the AI lifecycle.
The future of enterprise AI will not be defined by a single model or vendor.
Organizations will operate fleets of specialized models, autonomous agents, domain-specific knowledge systems, increasingly complex AI workflows.
Success will depend on the infrastructure that connects, control and secure these components.
Chrysent is building that infrastructure, not another AI application.
The operating layer for enterprise AI.