endorsedCompleted

Self-hosted LLM & MLOps in private AWS for UK HealthTech

Services Covered:

AI and Machine Learning • Cloud Consulting and Services • DevOps

Industry

Software Development

2 months

Budget

10K - 49K

Start Date

1 December 2025

Team Size

1-5

Engagement Model

Offshore

Project Capability Score (PCS)

82/100

Strong

Project Capability Score (PCS) estimates how capable Honeycomb Software is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

Sonomics

Barcelona, Spain

Project Summary

Honeycomb Software implemented a secure, scalable AI infrastructure for a custom software engineering firm (Sonomics) to enable a HealthTech client’s self-hosted LLM within a private AWS environment. They delivered MLOps architecture, CI/CD/GitOps pipelines, GPU autoscaling (scale-to-zero), observability, and thorough runbooks to meet UK data residency and compliance requirements. The work produced a production-ready, compliant LLM capability with clear handover documentation.

Key Challenges

Build a secure, scalable AI architecture the client can independently operate and expand
Run an LLM entirely inside the client's private AWS environment
Meet strict UK data residency and compliance requirements by keeping all AI processing and storage within the client's controlled infrastructure
Minimize GPU infrastructure costs while ensuring production readiness and observability

Project Deliverables

Kubernetes-based deployment of an open-source LLM in the client's private AWS environment
MLOps architecture design and environment setup
CI/CD pipelines and GitOps workflows for automated model deployments
Kubernetes/GPU node management and scale-to-zero autoscaling policies
Inference observability (metrics, logs, alerting) and operational runbooks
Structured handover and documentation

Project Solution

Acting as a specialist subcontractor, Honeycomb designed and implemented a Kubernetes-based deployment of an open-source LLM within the client’s private AWS environment. They provided MLOps architecture and environment setup, CI/CD pipelines and GitOps workflows for repeatable deployments, Kubernetes/GPU node management with scale-to-zero autoscaling to cut idle GPU costs, and an inference observability stack with metrics, logs, and alerting. The engagement included operational runbooks and a structured handover so the client’s team could operate and extend the platform independently.

Project Outcome

Compliant, production-ready self-hosted LLM running entirely within the client's UK AWS environment with no external API dependencies
Reduced idle GPU costs via scale-to-zero autoscaling
Full observability enabling confident production management of inference workloads
Clean handover and documentation allowing the client to operate and extend the platform independently
All deliverables were completed on time with clear communication and risk flagging

Platforms

Cloud

Tech Stack

Amazon Web Services (AWS)
Kubernetes

Client Endorsement

Overall Review Rating

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“Honeycomb Software successfully delivered the project, enabling the client to have a compliant, production-ready self-hosted LLM capability. The team communicated clearly, took ownership of their deliverables, and flagged risks early. Their quality of handover documentation stood out.”
Iryna Stakhiv
BDM
Date: 03/17/2026