Advisory

Know what to build before you build it.

Most failed AI and data programs don't fail in engineering — they fail in framing. Our advisory practice gives you the framing: what's worth building, what your data can actually support, and the sequence that de-risks the rest. Delivered by architects who build, not analysts who observe.

21+ yrs of enterprise technology experience behind every recommendation
2 wks fixed-scope AI Readiness Assessment — findings you can execute
0 slideware deliverables — blueprints and roadmaps, not decks
Advisory methodAdvisory method: discover the business problem and data estate, analyze gaps and opportunities, blueprint the target architecture, and produce a sequenced roadmap. AnovaCloud advisory method evidence synthesis commitment DISCOVER interviews · data inventory constraint mapping ANALYZE opportunity scoring gap & risk analysis BLUEPRINT target architecture build / buy decisions ROADMAP sequenced initiatives effort & ownership FIG. 01 — THE ADVISORY METHOD: EVIDENCE IN, EXECUTABLE PLAN OUT

Every advisory engagement follows the same spine — no bespoke process theater.

What we do

Advisory offerings

01

AI Readiness Assessment — 2 weeks

A fixed-scope, two-week answer to "where should AI actually go in our business — and are we ready?"

  • Opportunity map scored on value, feasibility, and data readiness
  • Data-gap analysis: what must be true before each use case works
  • Sequenced roadmap with build/buy calls and effort sizing
Request this assessment →
02

Data Strategy & Roadmap

For organizations whose data estate grew by accident: a target-state architecture and a pragmatic path to it.

  • Current-state audit: platforms, pipelines, ownership, and cost
  • Target architecture with platform decisions and data contracts
  • Phased migration plan that keeps the business running
Discuss your data estate →
03

Architecture Review & Health Check

An independent second opinion on a platform, pipeline, or AI system — before it becomes a postmortem.

  • Deep review of architecture, code, data flows, and operations
  • Risk register ranked by blast radius, not vibes
  • Remediation plan your own team can execute
Book a health check →
04

Build-vs-Buy & Vendor Evaluation

Vendor-neutral guidance on platform selection — from someone who has implemented both sides of the shortlist.

  • Requirements weighted by your constraints, not analyst quadrants
  • Structured evaluation with reference checks that ask real questions
  • Total-cost modeling including the engineering you don't see in the quote
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Engagement models

How advisory engages

ModelFormatBest for
Advisory call 90 minutes, fixed fee Framing a problem, gut-checking a plan, unblocking a decision
Assessment 2–3 weeks, fixed scope AI readiness, migration scoping, architecture review — with a written blueprint
Workshop Half or full day, on-site or remote Aligning leadership and engineering on one roadmap
Embedded advisor Monthly cadence Ongoing architecture guidance while your team executes

FAQ

Advisory, answered

Our assessments are done by the same architects who build the systems — 21+ years of enterprise technology experience. Deliverables are executable blueprints and sequenced roadmaps, not decks. Fixed scope and fixed timeline, agreed up front.
Two weeks: stakeholder interviews, data-estate inventory, opportunity mapping against business value, data-gap analysis, and a sequenced roadmap with build/buy recommendations and rough effort sizing.
Regularly. If the data isn't there, the ROI doesn't pencil out, or a simpler approach wins, we say so in writing. An assessment that only ever recommends building is a sales document.
Yes — Assess → Architect → Deploy is our standard spine. But advisory deliverables are yours to execute with anyone; there is no obligation to continue with us.
A 90-minute advisory call to frame the problem. If there's a fit, we scope a fixed-timeline assessment. Talk to an architect to begin.

Start here

Get the framing right, then build with confidence.

Ninety minutes with an architect. Bring the problem; leave with a point of view — whether or not we work together after.