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

A chatbot isn't an intelligent system.

Generating an answer is easy. Getting AI to reliably complete a real workflow is an engineering problem.

Real-world systems need to understand context, choose the right action, interact with external tools, handle failures, respect permissions, and know when a human needs to take over.

We design the architecture around those requirements.

What We Build

From single-purpose tool-calling agents to multi-agent swarms with state and human oversight.

01 — AI AGENTS

AI Agents

Systems that can interpret goals, use tools, and execute multi-step tasks.

02 — MULTI-AGENT SYSTEMS

Multi-Agent Systems

Specialized agents working together through defined roles, state, and controlled handoffs.

03 — AI COPILOTS

AI Copilots

Context-aware assistants that help people make decisions and complete work faster.

04 — TOOL-CALLING WORKFLOWS

Tool-Calling Workflows

Connect AI reasoning to APIs, databases, SaaS platforms, and internal systems.

05 — AUTONOMOUS WORKFLOWS

Autonomous Workflows

Move repetitive processes from manual execution toward controlled AI-driven automation.

06 — HUMAN-IN-THE-LOOP SYSTEMS

Human-in-the-Loop Systems

Keep people in control of decisions where accuracy, risk, or business policy requires it.

How We Engineer Intelligent Systems

Treating agents as maintainable software — with evaluation, failure handling, and observability built in from day one.

01
UNDERSTAND

Map the workflow

Map the workflow, users, tools, data, permissions, and decisions.

02
DESIGN

Define the architecture

Define the agent architecture, responsibilities, state, tools, and boundaries.

03
BUILD

Connect the system

Connect models, retrieval, tools, APIs, memory, and workflow logic.

04
EVALUATE

Test reliability

Test task completion, tool selection, reliability, failure modes, latency, and cost.

05
OPERATE

Trace and improve

Trace execution, monitor behavior, review failures, and continuously improve.

💡 Production Note: This emphasis on treating agents as maintainable software — with evaluation, failure handling, and observability — is increasingly important in production AI.

The Production Layer

Intelligence needs engineering underneath it.

Context

Give systems the information they actually need.

Tools

Connect reasoning to controlled actions.

Guardrails

Define what the system can and cannot do.

Observability

Understand every important execution and failure.

Deliverables

What you receive upon handover.

Complete architecture, verified integrations, continuous tracing, and production code ownership.

✓Agent architecture
✓Tool integrations
✓Workflow orchestration
✓State and memory design
✓Evaluation framework
✓Human approval flows
✓Execution tracing
✓Production deployment
✓Documentation and handover
Case Study · Intelligent Workflow Automation

Intelligent workflow automation

The Challenge

A business workflow required people to repeatedly gather information from multiple systems and manually complete the next action.

What We Built

An agent-based workflow connecting structured tools, business rules, contextual retrieval, and human approval.

Engineering FocusAgents · Tools · Orchestration · State · Observability
View the architecture

Built with the right tools for the system.

We choose the architecture around the problem — not the framework.

Models

OpenAI · Gemini · Claude

Orchestration

LangGraph · Custom Engines

Backend

Python · FastAPI · TypeScript

Data

PostgreSQL · Qdrant

Infrastructure

Docker · Kubernetes · AWS

What should your AI system actually be able to do?

Tell us about the workflow. We'll help determine what should be automated, what should remain human-controlled, and what it takes to make the system reliable.

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