AI application integration
Connect inference to real workflows, data access and application interfaces. Define what the model receives, what it can return and what happens when the result cannot be used.
AI engineering beyond the model call.
We integrate AI into applications and data systems, and work on the performance underneath them. Model behaviour, evaluation and compute costs are part of the same engineering problem.
Connect with the teamWhat we engineer
Evaluation and data
Establish a task-specific baseline and representative evaluation examples. Track changes in data, prompts and models so a result can be explained and reproduced.
Inference and GPU performance
Profile the workload before choosing an optimisation. Examine memory movement, kernel execution, batching and the trade-offs between latency and throughput.
Language-model research
Research training and improving compact language models within a fixed compute budget. Keep experimental ideas separate from measured results and application commitments.
The decisions that shape the system
What counts as a useful answer?
Define task quality and unacceptable outputs before comparing models. A benchmark score is only useful when it relates to the application.
Where does the workload spend its time?
Separate model execution from retrieval, networking and application overhead. Optimise the bottleneck that affects the user.
What should remain under human control?
Define data access, tool permissions and review points. An AI integration should fit the system’s existing security boundaries.
System building blocks
- AI integration and data-flow design
- Evaluation baseline and failure cases
- Inference profiling and optimisation plan
- Deployment and monitoring requirements
GPU kernels on Blackwell SM120
Our TileLang kernel work targets NVIDIA RTX PRO 6000 Blackwell. A measured memory roofline of 1.63 TB/s gives us a hardware reference for profiling. It is a hardware measurement, not a promised application speedup.
Read about our researchBuild on the work. Join the conversation.
For product questions, technical collaboration or feedback on our published work, get in touch with Horizon Tech.
Connect with Horizon Tech