production systems / audit-ready delivery

Enterprise software systems for reliable digital operations.

Savant Realms helps enterprise teams reduce incidents, control cloud spend, modernize backends, and ship AI-enabled systems with agent orchestration, MCP integrations, and production guardrails.

Lombardy, Italy Remote-first delivery Cloud cost guardrails AI agents & MCP
sr-ops://engagement/runbook
> git checkout -b harden/payments-api && make architecture-review SERVICE=payments-api RISK=high reviewed
> terraform plan -var-file=prod.tfvars -target=aws_iam_role.agent_runtime planned
> pnpm test:agents --mcp --evals --tool-permissions=strict passing
> kubectl rollout status deploy/api && aws cloudwatch get-metric-data --metric latency_p95 stable
# every change: reviewed → planned → tested → rolled out
// operating model

Senior engineering for systems that cannot drift.

We work with teams that need clear architecture, reliable delivery, fewer production surprises, and AI systems that are useful without becoming ungoverned automation. The job is not to add ceremony. The job is to expose risk, ship clean changes, and leave the system easier to operate.

Expect direct technical feedback, pragmatic implementation, and runbooks that recruiters, sales teams, auditors, and engineers can all understand: what changed, why it matters, what agents can do, and how it behaves under load.

// reduce
incidents Make failure modes visible before customers find them.
// control
cloud cost Remove idle spend, set guardrails, and document ownership.
// modernize
backends Untangle legacy flows without breaking core revenue paths.
// orchestrate
agents Design AI workflows with tool permissions, MCP servers, evals, and rollback paths.
// capabilities

Engineering modules, not slideware.

Focused consulting and implementation for enterprise teams that need measurable reliability, lower operational drag, secure AI adoption, and infrastructure that survives audits.

// application engineering

Software engineering

Build new systems from zero, ship features into ones already carrying load, and stabilize what has gone brittle — often all three inside one engagement. Domain modelling, typed contracts, versioned APIs, reversible migrations, tests that fail for the right reason, and release paths that roll back. Legacy work moves incrementally behind a boundary rather than in a rewrite nobody can schedule — front to back, from schema to the interface people actually use.

  • Java · Spring · Quarkus
  • Python · Django · Flask · FastAPI
  • TypeScript · Node · Express
  • PHP · Laravel
  • .NET 8 · C#
  • React · Angular · Vue
  • Next.js
  • Prisma · SQLAlchemy
  • Relational DBs
  • Document & graph DBs
  • JUnit · Jest · pytest
// integration reliability

Systems integration

Connect ERPs, SaaS tools, partner APIs, payment providers, data feeds, and internal platforms — contract-first, versioned, and event-driven where that earns its keep. Retries, idempotency keys, dead-letter paths, replay, and monitoring on every boundary, with one named owner per integration, so a partner outage degrades instead of cascading.

  • REST · GraphQL
  • Contract-first APIs
  • Kafka
  • AWS SQS · SNS
  • Step Functions
  • Webhooks · callbacks
  • Retries · idempotency
  • Salesforce · CRM sync
  • Braintree · PayPal
  • Entra ID · MSAL
// cloud native

Cloud infrastructure

Design and harden AWS, Azure, and GCP estates: infrastructure as code, least-privilege access, backup and restore posture that has actually been tested, right-sizing, and spend visibility per team. Environments rebuildable from the repository, deployments that roll back cleanly, and a bill nobody is afraid to open.

  • AWS
  • Azure
  • GCP
  • Terraform · CloudFormation · CDK · Pulumi
  • Lambda · serverless
  • S3 · object storage
  • Docker · Kubernetes
  • GitLab CI · GitHub Actions
  • CloudWatch · Sentry
// ai agent orchestration

AI systems

Agentic development, MCP servers, tool permissioning, eval suites, retrieval flows, and automation that respects audit, security, and human review.

  • MCP
  • Agent orchestration
  • LangChain · LangGraph
  • RAG · embeddings
  • Evals · tool permissions
  • Context engineering
// technical consulting

Technical consulting

Architecture reviews, production debugging, due diligence, delivery planning, and team coaching from engineers who will say what is broken.

  • Architecture review
  • Production debugging
  • Due diligence
  • Delivery planning
  • Scrum · Kanban
// architecture patterns

Composable systems for modern software teams.

Every engagement has a different shape. This map shows the layers we design, modernize, integrate, or operate: clients at the edge, the access tier in front of them, application and AI services, the data and integration behind those, and the platform they all run on.

01 clients
Web apps browser clients and internal tools
Mobile clients native and hybrid front ends
Partner systems B2B and machine-to-machine
02 edge & access
CDN & WAF caching, TLS, edge rules
API gateway routing, rate limits, versioning
Identity & authorization OAuth2, OIDC, tenant scoping
03 application & AI
Domain services typed contracts, testable boundaries
Agent runtime MCP tool servers, retrieval
Eval & permission gates evals, tool scopes, human review
04 data & integration
Relational transactional records of truth
Document & graph flexible and connected data
Cache read paths and session state
Events & queues async work, retries, idempotency
Object storage files, exports, backups
05 platform & operations
IaC & CI/CD reproducible, rollback-ready releases
Containers & orchestration isolation and scale when earned
Metrics, logs & traces failure modes visible before customers
Audit trail & cost guardrails who changed what, and what it spends
// contact

Let's get in touch

Legacy platform dragging delivery? Cloud bill climbing? Integration failing silently? AI roadmap stuck between demos and production? Send the problem and we will map the first production-safe move.