01
AI Infrastructure
Put AI to work in your products and operations on infrastructure built to run it reliably.
A promising AI demo is the easy part. Running models reliably, securely and at a sensible cost is where most initiatives stall. We build the infrastructure that gets AI into production.
From connecting large language models to your own data, to serving models behind your applications and monitoring their quality, we design the stack around your use case and budget.
02
03At a glance
At a glance
- Workloads
- LLM · ML
- Deployment
- Cloud or on-prem
- Model quality
- Monitored
04
What's included
LLM integration
Assistants, search and automation built on large language models and your own data.
Vector search & RAG
Retrieval pipelines that ground AI answers in your documents and records.
Model serving
Scalable, cost-aware hosting for models behind your applications and APIs.
MLOps & monitoring
Versioning, evaluation and monitoring so model quality holds up over time.
05
How we deliver it
- 01Identify
We pick the use cases where AI adds real value and check your data is ready.
- 02Prototype
A working proof of concept validates quality, cost and feasibility quickly.
- 03Productionize
The solution moves onto robust, monitored infrastructure your team can run.
06
What you get
- —AI features that work in production
- —Answers grounded in your own data
- —Predictable running costs
- —Infrastructure your team understands
07
Have a ai infrastructure project in mind?
Talk to the Cognisync team. We reply within one business day.
08