Cerebral Hacks Logo
Cerebral Hacks

AI engineering for systems that need to work.

We design, build, and deploy AI systems around real business workflows — from intelligent agents and enterprise knowledge systems to the infrastructure that runs them in production.

Talk to our engineersExplore services
Image 1
Image 2
Image 3
Image 4
Image 5
Image 6
Image 1
Image 2
Image 3
Image 4
Image 5
Image 6
Image 1
Image 2
Image 3
Image 4
Image 5
Image 6
Image 1
Image 2
Image 3
Image 4
Image 5
Image 6

Getting AI to work once is not the hard part.

Production systems need to answer harder questions:

  • How accurate is it?
  • How does it behave when it fails?
  • How much does every request cost?
  • Can we trace what happened?
  • Can it handle real traffic?
  • Is sensitive data protected?
  • Can we safely change the model?

That's the engineering layer we build.

What We Build

From cloud architecture and inference optimization to automated regression testing and prompt defense.

01 — AI INFRASTRUCTURE

AI Infrastructure

Cloud architecture, deployment systems, compute, APIs, containers, and orchestration.

02 — MODEL SERVING & INFERENCE

Model Serving & Inference

Optimize how models are deployed and served for latency, throughput, and cost.

03 — AI EVALUATION

AI Evaluation

Build repeatable evaluation systems for quality, accuracy, reliability, and regression testing.

04 — OBSERVABILITY

Observability

Trace requests, model behavior, latency, cost, failures, and system health.

05 — AI SECURITY

AI Security

Protect AI applications against data leakage, misuse, prompt injection, and unauthorized access.

06 — GOVERNANCE

Governance

Create controls around models, data, access, evaluation, and operational behavior.

The Production AI Stack

A resilient multi-layer architecture designed for high reliability and zero downtime.

APPLICATION
Agents · RAG · AI Products
AI CONTROL
Evaluation · Guardrails · Governance
AI RUNTIME
Model Serving · Inference · Routing
DATA
PostgreSQL · Vector DB · Data Pipelines
INFRASTRUCTURE
Docker · Kubernetes · Cloud · GPU
OBSERVABILITY
Tracing · Metrics · Logs · Cost

How We Take AI to Production

A disciplined transition from unmonitored scripts to hardened cloud services.

01 — ASSESS

Understand current workload

Understand the current system, workload, risks, and constraints.

02 — BENCHMARK

Measure baseline metrics

Measure quality, latency, throughput, cost, and failure modes.

03 — HARDEN

Harden reliability & security

Improve architecture, security, evaluation, and reliability.

04 — DEPLOY

Automate production CI/CD

Create repeatable production infrastructure and deployment pipelines.

05 — OBSERVE

Active health monitoring

Monitor system behavior and identify failures before they become business problems.

06 — OPTIMIZE

Continuous performance tune

Continuously improve performance, quality, and cost.

Production Deliverables

Everything required to scale securely.

Automated CI/CD pipelines, container orchestration, cost guardrails, and compliance logs.

✓Deployment architecture
✓Model serving
✓Inference optimization
✓Evaluation framework
✓Regression testing
✓Observability
✓AI security controls
✓Guardrails
✓Cost monitoring
✓CI/CD
✓Cloud infrastructure
✓Operational documentation
CerebralHacks Engineering Project · Production Hardening

From prototype to production.

Starting Point

A working AI prototype with limited evaluation and operational visibility.

Engineering Challenge

The system needed predictable performance, measurable quality, and production controls.

What We Changed

Architecture → evaluation → infrastructure → observability → security.

Outcome

Sub-200ms p95 latency, 99.9% uptime, automated regression testing on every PR, 45% inference cost reduction, zero prompt injection vulnerabilities.

Cloud Architecture · Model Serving · Observability · Security GuardrailsTalk to our engineers

Your AI works. Is it ready for production?

Bring us the prototype, architecture, or problem. We'll help identify what needs to change before real users depend on it.

Talk to our engineers
No sales pitch·Technical conversation·Clear next steps