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PORTFOLIO / SYSTEMS IN PRACTICE

A closer look at what we are building.

Our portfolio documents public product development, internal engineering systems, and representative architectures that show how Cerebrix approaches production AI.

These are capability demonstrations and systems in development—not invented client case studies. Client-specific work may remain private.

SELECTED SYSTEMS / 04

Designed around workflows, evidence, and operating control.

Each system combines model intelligence with software, data access, validation, and clear boundaries.

01

PUBLIC PRODUCT / IN DEVELOPMENT

Autonomous Email Operations Agent

An email agent that interprets incoming requests, retrieves company-specific knowledge, drafts grounded responses, and coordinates the next action under defined operating rules.

DATA
CONTEXT
TOOLS
REASONING
VALIDATION
ACTION
CEREBRIXSYSTEM
THE OPERATING CHALLENGE

Teams lose time classifying repetitive email, locating the right policy or account context, and preparing consistent responses.

SYSTEM COMPONENTS
  • Intent and urgency classification
  • Permission-aware RAG retrieval
  • Evidence-backed response drafting
  • Approval and escalation routing
  • Action logs and outcome monitoring
CONNECTED CAPABILITIES
AI AgentsRAG SolutionsPrompt EngineeringSoftware Testing
02

REFERENCE ARCHITECTURE

Enterprise Knowledge Assistant

A citation-first knowledge system for policies, procedures, technical documentation, and institutional information across fragmented repositories.

SOURCES
PARSE
INDEX
RETRIEVE
RERANK
ANSWER
CEREBRIXSYSTEM
THE OPERATING CHALLENGE

Employees cannot reliably find current answers across shared drives, wikis, PDFs, ticket histories, and internal applications.

SYSTEM COMPONENTS
  • Source ingestion and normalization
  • Hybrid retrieval and reranking
  • Access-aware answer generation
  • Inline citations and source inspection
  • Retrieval and groundedness evaluation
CONNECTED CAPABILITIES
RAG SolutionsCustom SoftwareSoftware Testing
03

CEREBRIX LABS / PROTOTYPE

Document Intelligence Workflow

A structured workflow that extracts, classifies, validates, and routes information from operational documents while escalating uncertain cases.

INPUT
CONTEXT
INSTRUCTION
TOOLS
SCHEMA
TEST
CEREBRIXSYSTEM
THE OPERATING CHALLENGE

Manual document review creates queues, inconsistent extraction, duplicate entry, and limited auditability.

SYSTEM COMPONENTS
  • Document parsing and classification
  • Schema-bound extraction
  • Rule and model validation
  • Confidence-based human review
  • System-of-record updates
CONNECTED CAPABILITIES
AI AgentsCustom SoftwarePrompt Engineering
04

INTERNAL PLATFORM / EVOLVING

AI Quality Evaluation Harness

A reusable evaluation environment for measuring retrieval quality, response behavior, tool execution, safety boundaries, latency, and regression risk.

WORKFLOW
CASES
EXECUTE
MEASURE
ANALYZE
RELEASE
CEREBRIXSYSTEM
THE OPERATING CHALLENGE

AI behavior changes across prompts, data, models, and tools, making traditional pass-or-fail testing incomplete.

SYSTEM COMPONENTS
  • Versioned evaluation datasets
  • Deterministic workflow checks
  • Model-graded quality rubrics
  • Failure clustering and inspection
  • Release comparison reporting
CONNECTED CAPABILITIES
Software TestingLLM EngineeringPrompt Engineering

PRIVATE WORK / BUILT TO FIT

Your system will be specific to your organization.

Production engagements begin with your workflow, users, knowledge, systems, constraints, and quality requirements. The result may reuse proven architectural patterns, but the implementation is designed around the environment where it must operate.

See how we work

LET'S DEFINE THE RIGHT SYSTEM

What should we build for your team?

Bring us the workflow, knowledge problem, or software requirement. We will help shape it into a system that can be designed, evaluated, and operated responsibly.

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