AI Coding Agent for Enterprise
Deploy a secure Agentic Harness within your organisation to govern how AI coding agents operate across your development lifecycle.
What is an AI Coding Agent for Enterprise?
AI Coding Agent for Enterprise is the deployment of an Agentic Harness within your organisation — a structured framework that governs how AI coding agents operate across your development lifecycle. Whether you are working with frontier tools such as Claude Code, Codex, or Gemini, or evaluating open-source solutions, we configure the agent's skills, enforce security guardrails tailored to your regulatory environment, and design the system architecture that makes AI-generated code maintainable and auditable.
The engagement centres on knowledge transfer. Your engineering teams walk away self-sufficient, owning the harness and compounding its value with every sprint.
governance pillars
weeks of training
knowledge transfer
Four governance pillars
The difference between AI-assisted engineering and AI-generated slop is not the model — it is the governance around it.
Specifications
We establish the Explore, Plan, and Execute workflow. The agent maps your codebase, produces a structured plan that human engineers review, then executes with deterministic tests validating every output.
Agentic Setup
Project Skills defining how your project works, a layered Configuration Hierarchy spanning IT/project/user levels, MCP Servers linking agents to your internal tools, and Sandbox & Hooks enforcing credential isolation and controlled execution.
Security for Regulated Environments
DevSecOps principles applied to AI-generated code: destructive command containment, credential isolation, supply chain attack prevention, production environment isolation, and hard execution and budget limits.
System Design
Stack and pattern definition: modular architecture, vertical slices, co-located tests. Deterministic guardrails and architectural decisions encoded into boilerplates so the agent extends your established patterns.
Engagement Model
Architecture Sprint
One week. We analyse your SDLC, define your system design and deliver a roadmap covering short-term quick wins and long-term vision.
Team Training
Four to eight weeks. Online learning platform followed by collaborative workshops to customise the harness against your own SDLC and codebase.
Advisory Retainer
Ongoing engagement. Agentic reviews, security audits and methodology updates to keep pace with the rapid evolution of AI engineering.
Prerequisites
An inventory of development tools, IDEs, and repositories; security and compliance requirements for code generation; access to your codebase and CI/CD pipeline for the architecture sprint; and a designated technical lead on the client side.
Financial services
Agentic Harness deployment under strict regulatory constraints
A financial services firm wanted to accelerate its development velocity by adopting AI-assisted coding, but faced strict regulatory constraints on data handling and code provenance.
Tomeris deployed the Agentic Harness: we assessed available AI coding agent solutions, configured a deployment that kept sensitive financial data outside the model's context, built project skills encoding the firm's architectural patterns, and integrated sandboxed execution with credential isolation into existing workflows.
After a four-week team training programme, the engineering team owned the harness autonomously. Developer velocity increased measurably, with maintainable, auditable code produced within the firm's compliance boundaries.
Security guardrails were enforced through configuration: repository-level access controls, code review gates for AI-generated suggestions, command deny lists for production environments, and audit logging of all agent interactions.
Results
Ready to deploy AI in your development lifecycle?
Book a discovery call and let's discuss setting up an Agentic Harness tailored to your organisation.