AI Engineering & Research Consultancy
Engineering AI
beyond the API.
7 Hidden Layers partners with organizations to design, optimize, and deploy production-grade AI systems — from strategy and model architecture to inference infrastructure.
Trusted by ambitious startups and engineering teams
Capabilities
What we do.
AI Strategy
Where to apply AI, what to build, and what to buy. We help leadership teams make model, vendor, and infrastructure decisions grounded in engineering reality.
Roadmaps · Build vs. buy · Model selection
AI Systems Engineering
End-to-end design and construction of production AI systems: retrieval pipelines, multi-agent architectures, evaluation harnesses, and the software around the model.
RAG · Multi-agent systems · Evaluation
Model Optimization
Fine-tuning, distillation, and small language models. We shrink cost and latency while holding the quality bar — often replacing frontier APIs with models you own.
Fine-tuning · Distillation · SLMs
Inference Infrastructure
Serving stacks engineered for throughput and cost: quantization, batching, cache strategy, and GPU-aware deployment on your cloud or your own metal.
vLLM · TensorRT · Quantization
Enterprise AI
AI that survives procurement, security review, and scale. On-prem and VPC deployments, compliance-conscious architectures, and systems built for regulated industries.
On-prem · VPC · Governance
Research & Prototyping
When the answer isn't in a paper yet. We run focused applied-research sprints to de-risk the hard question before you commit engineering budget to it.
Applied research · De-risking · Sprints
The difference
Depth is the difference.
Anyone can call a model. Making AI systems fast, accurate, and economical at scale is an engineering discipline — and it is where we spend our time.
Common practice
- API integrations
- Chatbots
- Prompt engineering
- Workflow automation
- Quick MVPs
Our practice
- Model architecture
- Fine-tuning, distillation & SLMs
- Inference optimization
- GPU-aware deployment
- Enterprise-scale performance engineering
Technical depth
We work the whole stack.
Application code is the visible tenth of an AI system. Most engagements stop three layers in. Ours span all ten — because the lower layers decide whether a system is fast, affordable, and yours.
Approach
How an engagement runs.
Discovery
We map your product goals, constraints, data, and current stack. No slideware — we read the code.
Architecture
System design across models, retrieval, and infrastructure, with cost and latency budgets set upfront.
Prototype
A working system on your data within weeks, instrumented with evaluation from day one.
Optimization
Fine-tuning, distillation, quantization, and serving work until quality, latency, and cost targets hold.
Production deployment
Shipped into your cloud or on-prem environment, with observability and failure modes engineered in.
Continuous improvement
Models drift and workloads grow. We stay engaged to keep the system fast, current, and cheap to run.
Selected work
Judged by what we ship.
We are documenting recent engagements. Until then, we would rather walk you through the work directly — the systems, the numbers, and the trade-offs.
Case studies in documentation — available on request
Ask about our workTooling
The stack we speak fluently.
Contact
Let’s build AI systems that last.
Tell us what you’re building. We’ll tell you honestly whether we can help.