Applied AI systems / product engineering

GrafittoAI

We turn messy software, data, and model behavior into operating surfaces that teams can read, trust, and evolve.

  • Neural orchestration
  • Datacenter-aware architecture
  • Observable product delivery

System blueprint

Design language built from the work itself: networks, infrastructure, telemetry, and release paths.

Neural fabric

Decision paths are drawn as layered graphs, not abstract glow.

Infrastructure plane

Compute, queues, storage, and delivery are visible as a topology.

Operational loop

Every section maps to the same trace: signal, model, service, outcome.

Working principle

The interface is not the decoration. It is the place where architecture, intelligence, and business pressure become legible.

Core services

Built for enterprise trust and high-velocity delivery.

01

Custom platform engineering

Product-grade software for teams that cannot afford fragile systems.

  • Symfony 8 platforms
  • API-first systems
  • CQRS where it pays off

02

AI implementation

LLM, agent, and automation programs that move beyond prototypes.

  • Agent orchestration
  • RAG and data pipelines
  • Model evaluation

03

Cloud architecture and DevOps

Infrastructure that scales horizontally without becoming a second product.

  • Container platforms
  • Redis and queues
  • Zero-downtime deploys

04

Long-term technical consulting

A senior engineering partner for architecture, delivery, and technical decisions.

  • Architecture reviews
  • Delivery governance
  • Security posture

AI capability explorer

From opportunity mapping to observable production systems.

AI opportunity mapping

We identify workflows where LLMs, agents, and automation create defensible operational leverage, then define risk controls and ROI metrics before build starts.

  • Use-case scoring
  • Data readiness
  • Risk model

Production implementation

We ship retrieval, tool use, queue-backed automations, model routing, and evaluation harnesses inside maintainable Symfony applications.

  • RAG pipelines
  • Agent tools
  • Evals

Observability and improvement loops

We instrument prompts, data access, costs, latency, and human review outcomes so the system improves safely after release.

  • Quality dashboards
  • Cost controls
  • Feedback loops

Measured impact

Case studies with operational numbers attached.

All case studies

Insurance

Agent-assisted claims triage with human review

A queue-backed LLM workflow classified documents, prepared summaries, and routed exceptions to specialists.

  • 62% faster first review
  • 41% fewer manual routing errors
  • 3.8x more consistent summaries

Technical thinking

Notes on AI systems, Symfony architecture, and performance.

Have a difficult system decision ahead?

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