LLMOps Services
LLM operations is the discipline that makes generative AI systems manageable and auditable in terms of costs, token use, and decision-making.
What can you get?
Set up version control for prompts, so you can track, test, and roll back changes just like code. Ask us for integrated A/B testing and experiment tracking, which will give you clarity on what’s working and why. We can help you apply model routing strategies, so simple queries don’t unnecessarily hit large, expensive models.
Build automated guardrails into your system to flag PII leaks, toxicity, jailbreak attempts, and hallucinations before they reach end-users. Combined with role-based access, input validation, and rate limiting, your system can become safer and more compliant with our help. Protect your LLMs against unintentionally generating biased or sensitive content, as well as guard the data of your users.
Important: For critical systems where sending data to external LLM providers like OpenAI is not an option, we can help you deploy a small-scale open-source model hosted exclusively within your own infrastructure. Ask us about it.
Ask us about implementing full audit traces, so you always know which prompt, model, and user produced which output.
Make sure each deployment is repeatable, reviewable, and auditable through versioned scoring scripts, tracked model artifacts, and automated test harnesses.
LLMs can become surprisingly expensive, fast. We give you full visibility into usage (by user, by service, or by session), so you can measure true cost impact. With spike alerting and batching or caching strategies, we help you reduce waste and stay in control of your budget.
Let’s build infrastructure that scales with CI/CD for prompts and models, real-time monitoring, and anomaly detection. By introducing architectural optimization techniques, we can reduce downtime and prevent performance bottlenecks.
Fast iteration is a competitive advantage. With testable prompt templates, automated evaluations, rollback support, and tracked experiments, your team can ship updates safely and frequently. Let’s embed these workflows into your development process.
What Our Clients Say About Us?
LLMOps Helps Your Team Collaborate, Take Control of Costs and Scale LLMs Across the Company
Shared Visibility
Everyone can trace which prompt, model or configuration generated a specific output.
Clear Handoff Points
Engineers can integrate prompts and models with confidence, while data scientists focus on iteration and testing.
CI/CD for Everyone
Automate deployments and rollback across environments, so no one is blocked waiting for “the ML person.”
Version Control for Prompts, Models, and Applications
Enable structured experimentation and safe collaboration without overwriting or losing work.
Collaborative Evaluation Loops
Product managers and reviewers can give structured feedback that feeds directly into improvements.
Optimize Costs
Keep using LLMs and agents without compromising on cost, latency, or accuracy.
Grow Without Worry
Implement solutions like prompt caching and Intelligent Prompt Routing to ensure consistent performance and cost optimization as usage grows.
We’re an Official AWS Partner
Our team is recognized by Amazon Web Services, so if you work with Amazon Bedrock, we can help you use this AWS-native tools and reduce cloud costs, automate more of the LLM lifecycle within AWS, and align your LLMOps with best practices recommended by AWS.
Our AI Development Capabilities Include
Move LLM-based Agents from Your Laptop to Production with DAC.digital
LLMOps gives you the control, visibility, and automation your LLM-powered product needs to scale without breaking.
Let’s connect!
Send us an e-mail: [email protected]