AI-Native Engineering Company

From legacy systems to production AI.

AnovaCloud modernizes the platforms you run on, builds the AI systems you need next, and scales the team that owns both — strategy to production, backed by 21+ years of enterprise technology experience.

Depth21+ years of enterprise technology experience
Businesses6, one team
Based inFrisco, Texas
Data-to-agent pipelineData-to-agent pipeline: sources feed a lakehouse, which feeds a RAG layer, which powers AI agents, producing governed outcomes. An eval and guardrails layer sits under the agents. AnovaCloud data-to-agent reference pipeline ingest index retrieve act · audit SOURCES apps · DBs · APIs · docs LAKEHOUSE bronze → silver → gold RAG LAYER embeddings · vector index AGENTS planner · tools · memory OUTCOMES governed · measured EVAL + GUARDRAILS policy · red-team · audit log FIG. 01 — THE ANOVACLOUD DATA → AGENT PIPELINE

What we do

Three ways we move your business forward.

Modernize what you run. Build what you need next. Scale the team that owns it. Start with one pillar or the full arc — we meet you where you are.

The journey

Six chapters. One engineering motion.

Every engagement moves through the same spine — from data foundations to AI systems your people and your agents can run. Pick the chapter where you are; we meet you there.

01 — AI

Agents that do work, not demos

We design, build, and govern production AI agents — retrieval-grounded, tool-using, and evaluated before they ever touch your customers.

  • RAG systems over your data with citations, not hallucinations
  • Multi-agent workflows with eval harnesses and guardrails
  • From pilot to production with audit trails and rollback plans
Explore Agentic AI →
02 — Data

Data platforms AI can actually use

AI is only as good as the data behind it. We build lakehouses and pipelines with contracts, lineage, and quality gates — the unglamorous work that makes models trustworthy.

  • Lakehouse architectures on Databricks, Snowflake, and open table formats
  • Governed pipelines with data contracts and observability
  • Semantic layers so agents and analysts agree on what numbers mean
Explore Engineering →
03 — Cloud

Cloud foundations that scale without drama

Landing zones, platform engineering, and cost discipline — cloud architecture designed by people who have carried the pager.

  • AWS-centric architectures with infrastructure-as-code from day one
  • Platform teams and paved roads, not ticket queues
  • FinOps baked in: budgets, alerts, and rightsizing as routine
Explore Engineering →
04 — Modernization

Escape legacy without the big-bang rewrite

We migrate the databases and applications everyone is afraid to touch — with compatibility analysis, cutover plans, and zero-surprise weekends.

  • SQL Server and Oracle → PostgreSQL migrations, de-risked
  • Strangler-pattern application modernization
  • Fixed-scope assessments before anyone writes a migration script
Explore Modernization →
05 — Training

Your team, leveled up by practitioners

Corporate training taught by engineers who ship — bootcamps and workshops on agentic AI, data engineering, and database migration, tuned to your stack.

  • Hands-on bootcamps, not slideware — labs on your tooling
  • Role-based paths: engineers, architects, and leaders
  • Private cohorts with your data and your use cases
Explore the Academy →
06 — Workforce

Humans + AI, staffed as one team

We embed vetted data and AI engineers into your teams — and design the human-plus-agent operating model around them.

  • Vetted data, cloud, and AI engineers, embedded in your rituals
  • Team topologies that pair humans with agents productively
  • Build-my-team flow: define the squad, meet them, start in weeks
Explore Workforce →

How we engage

Assess → Architect → Deploy → Adopt & Scale

A fixed spine for every engagement. Start small with a bounded entry offer; expand only when the evidence says so.

Assess

We map your data estate, AI opportunities, and constraints — and tell you what not to build.

Entry: 90-min advisory call · AI Readiness Workshop

Architect

Blueprint before build: reference architecture, data contracts, eval criteria, and a sequenced roadmap.

Entry: AI Readiness Assessment

Deploy

Our engineers ship alongside yours — pipelines, platforms, agents — with tests and runbooks, not handoffs.

Entry: Database Migration Assessment · Agent Accelerator

Adopt & Scale

Training and staffing so the capability stays when we leave — humans and agents, one operating model.

Entry: Private team bootcamps · Build my team

Why AnovaCloud

Practitioner depth, not slideware.

21+ years of enterprise technology experience in data & AI architecture — from warehouse to agents
6 integrated businesses — advisory, engineering, agentic AI, modernization, academy, workforce
1 architecture-obsessed team — blueprints before builds, evals before launches

We don't publish client logos, invented deployment counts, or uptime theater. Ask us for reference architectures instead — that's the work talking.

Productized offers

Fixed scope. Fixed timeline. No discovery-phase purgatory.

Advisory · 2 weeks

AI Readiness Assessment

Where can AI actually pay off in your business — and what has to be true in your data first? A two-week, evidence-backed answer.

Deliverables: opportunity map · data-gap analysis · sequenced roadmap · build/buy calls

Start with an assessment →

Agentic AI · 6 weeks

Agent Deployment Accelerator

One production-grade agent in six weeks: scoped to a real workflow, grounded in your data, wrapped in evals and guardrails.

Deliverables: working agent · eval harness · guardrail policy · runbook & handover

See how agents ship →

Modernization · 3 weeks

Database Migration Assessment

De-risk your SQL Server or Oracle → PostgreSQL move before committing: compatibility, effort, and a cutover plan with no surprises.

Deliverables: schema inventory · compatibility report · effort model · cutover plan

De-risk your migration →

Every engagement is fixed-scope, fixed-timeline — see all productized offers →

The knowledge engine

We publish how we think.

Patterns

Reference architectures

Production patterns we reuse: enterprise RAG, multi-agent systems, lakehouse foundations, database migration.

Browse patterns →

Insights

Field notes

Opinionated takes from real builds — tradeoffs, failure modes, and what we'd do differently.

Read insights →

Academy

Train your team

Bootcamps in agentic AI, data engineering, and PostgreSQL migration — taught by practitioners.

View courses →

Workforce

Staff the mission

Vetted data and AI engineers, embedded in your team — plus the human+AI operating model.

Meet the workforce →

Built from enterprise experience

21+ years of enterprise technology experience, distilled into how we work

AnovaCloud was founded by a technology leader with 21+ years of enterprise technology experience designing and delivering large-scale data, cloud, database, and AI systems. The leadership experience behind AnovaCloud spans FAANG-scale technology environments and complex transformation programs for some of the world's largest organizations across healthcare, financial services, automotive, manufacturing, and telecommunications.

  • Experience informing this methodology includes enterprise-scale data platforms, cloud migrations, and AI programs
  • Credibility you can inspect: patterns, blueprints, assessments, and open tooling — not founder marketing
  • Every engagement is practitioner-led: architects, not account managers
More about AnovaCloud →

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Bring us your hardest data or AI problem.

Thirty minutes with an architect — not a sales rep. We'll tell you plainly whether we can help, what it would take, and what to do if we can't.