As AI coding assistants grow more capable, enterprises face a key challenge: how to adopt them without compromising security or privacy. Most tools rely on cloud APIs, sending code and data outside company walls – a dealbreaker for industries handling sensitive IP or customer data.

So, how do we build a secure, enterprise-ready coding agent? 

Our approach: a solution that runs fully in the cloud or on-premises – keeping your IP protected. This post examines the challenges of on-prem deployment, the benefits of Cosine’s architecture, and how we directly address the concerns of integrating AI with enterprises.

Why Enterprises Demand Private, On-Prem AI Agents

CTOs and CISOs are eager to harness AI – but not at the cost of security or compliance. Here’s why private or on-prem AI agents are becoming the default choice:

1. Data Privacy and Compliance - sending proprietary code to third-party APIs can breach internal policies or regulations like HIPAA, GDPR, and SOC2. Many organisations – especially in finance, healthcare, and government – require that sensitive data stay on infrastructure they fully control. A private LLM ensures data never leaves the environment, making “no data exfiltration” the top enterprise requirement for AI adoption.

2. Full Control and Customisation - using public cloud AI means ceding control and risking vendor lock-in. With private deployments, companies own the full stack – from model tuning to deployment. This enables fine-tuning on internal codebases, strict access controls, policy compliance, and consistent behaviour.

3. Reliability and Cost Predictability  - public LLMs charge per use and can introduce latency or downtime. On-prem deployments run on dedicated infrastructure, offering lower latency, no surprise costs, and more stable performance at scale.

With these factors in play, it’s no surprise enterprises are flocking to private LLMs. But deploying them isn’t easy.

Challenges of Putting LLMs On-Premise

Hosting a modern coding agent on-premise effectively means running your own LLM, bringing several challenges:

1. Compute Demands - code-capable LLMs need serious hardware: multi-GPU servers (e.g., A100/H100) and high memory. Most enterprises don’t have this infrastructure on hand, and scaling it is costly.

2. Maintenance Overhead - with on-prem deployment, your team manages updates, tuning, and scaling. Staying current in a fast-evolving field requires ML expertise that many companies lack.

3. Model Optimisation - since commercial models like GPT-4 aren’t available locally, teams turn to open-source LLMs. These often need distillation or quantisation to run efficiently on limited hardware, without sacrificing performance.

4. System Integration - a coding agent must do more than predict text – it needs to run code, access repos, and integrate with tools like IDEs and Git. Building this ecosystem in-house is complex and time-consuming.

In short, on-prem AI offers control but adds complexity. Cosine bridges that gap – offering flexible, secure deployment with a fine-tuned model built for real-world coding environments.

Cosine's Approach: Cloud Flexibility with On‑Prem Privacy

We built Cosine, an enterprise-ready coding agent designed to run fully in the cloud or entirely on-prem, based on customer needs.

Cosine runs on our proprietary secure infrastructure. It’s a zero-maintenance setup – no VMs to manage, no GPU burden on local machines. Despite being cloud-based, it integrates smoothly with your tools (GitHub, Slack, Jira) for high performance and ease of use.

Need more isolation? We can deploy Cosine inside your VPC on AWS or Azure. You control the environment and use your preferred models or hardware. Cosine can even be fine-tuned to cloud-specific LLMs or GPUs,  keeping data inside your cloud account and behind your firewalls.

For maximum control, we also support on-prem deployment using open-source LLMs (like LLaMA 3 or CodeLlama) fine-tuned with Cosine’s coding intelligence. The model runs entirely on your hardware, ensuring no data ever leaves your network – ideal for strict compliance environments.

In all these scenarios, the key advantage is privacy and control. Your code repository and prompts are not sent to an external service outside your trust boundary.

By allowing deployment on custom hardware or cloud accounts, we’re empowering enterprises to adopt AI coding assistants without sacrificing security. In other words, you don't have to choose between innovation and compliance – you can have both.

Our agent runs in a completely isolated, sandboxed environment on the server side, ensuring no access to unauthorised resources and safe handling of code execution.

Think of Cosine like a server-side colleague; it has access only to the sources and tools you explicitly provide on the server, and all interactions with it are mediated through a secure interface.

The Future of Enterprise Architecture

The landscape of AI coding tools is rapidly evolving. Companies want the productivity gains of an AI software engineer, but not at the cost of leaking source code or breaching compliance.

At Cosine, we’re focused on building a secure, enterprise-ready agent that works where you work. By combining on-premise deployment options, rigorous sandboxing, and fine-tuned AI models, we offer a product that is truly built for your codebase, tackling the challenges that enterprises face when integrating AI.