A written recommendation
With the reasoning visible, so your team can challenge it.
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Data & AI consulting
Consulting for the decisions that come before the build.
Sometimes the useful deliverable is not code. It is a defensible answer to what to build, what to buy, what to fix first and what to stop doing. These engagements are fixed-scope, produce a written recommendation, and do not require hiring us to implement it.
- Fixed scope
- Written deliverable
- No build commitment
What you get
A decision you can defend.
Costs at your real volumes
Modeled for today and for how you'll grow.
A sequenced roadmap
Ordered by impact and dependency, with rough effort per item.
Honest unknowns
Including where we think you should not proceed.
Engagements
Four fixed-scope engagements.
Data maturity audit
A written assessment of your data stack and a prioritized roadmap, in 2 to 3 weeks.
Learn moreAI readiness appraisal
Which AI use cases your data can support, which are worth it, and what to fix first.
Learn morePrivacy & cookieless
Consent architecture, signal-loss audit and a first-party measurement plan.
Learn moreBuild vs buy advisory
Three-year cost modeled at your real volumes, vendors evaluated, lock-in priced.
Learn moreThe problem
Expensive decisions made on vendor input.
Data and AI decisions get made with the worst possible evidence: vendor demos, a competitor's conference talk, and an internal team too busy running the current system to evaluate alternatives. The results are predictable. A platform gets bought for a problem that was actually modeling. An AI initiative launches on data that cannot support it. A three-year contract gets signed on pricing that breaks at twice current volume. The cost of the wrong call dwarfs the cost of checking.
What an advisory engagement produces
What you receive.
- A current-state assessment based on your actual systems and data, not a maturity questionnaire
- A written recommendation with the reasoning visible, so your team can challenge it
- Cost modeling against your real volumes, including how it changes as you grow
- A prioritized roadmap sequenced by impact and dependency, with rough effort per item
- The risks and the honest unknowns, including where we think you should not proceed
- A working session with your team and leadership to pressure-test the conclusions
How we work
How we run it.
Step 1
Agree in writing the specific decision the engagement has to answer, before we start
Step 2
Review the real systems, data and costs rather than relying on described state
Step 3
Model the options against your volumes and constraints
Step 4
Present findings, take the pushback, and revise into a final recommendation
Typical stack
What it runs on.
- Architecture review
- Cost modeling
- Data profiling
- Vendor evaluation
- Roadmapping
Proof from our work
Teams we've built for.
120+ automations live
Tinuiti
Tinuiti manages advertising across Amazon, Walmart, TikTok, Instacart, and Criteo, but their teams were stuck with fragmented reporting and heavy manual work. TechEsthete rebuilt their data and automation backbone from scratch, creating a multi-source ETL pipeline and a unified BI framework that pulls every marketplace into one dashboard that stays current through the day.
Read the case study
50+ campaigns, one dashboard
BTR Media
BTR Media is a retail media platform that helps brands and agencies manage and optimize advertising campaigns across Amazon, Walmart, and Instacart. TechEsthete designed and built its centralized campaign management platform: the ETL pipelines, data model, dashboards and automation behind it.
Read the case study
Risk scores in 5 min
Protego
We were engaged to architect and build the complete backend data infrastructure behind Protego: SP-API integration, report ingestion, risk-signal normalization and the scoring pipeline.
Read the case studyFAQ
Common questions.
Will you recommend your own implementation services?
Only where we are genuinely the right fit, and the recommendation stands on its own either way. Several of these engagements have ended with us advising a client to buy a product, keep their current stack, or hire in-house rather than engage us. An advisory deliverable that always concludes "hire us" is a sales document, and it is worth nothing to you.
How long does an advisory engagement take?
Most run two to four weeks, depending on scope and how quickly we get system access. Tight, single-question engagements can be shorter. We scope it in writing up front, with a fixed quote, so there is no open-ended meter running.
Do we have to implement with you afterwards?
No. The deliverable is written to be actionable by whoever does the work: your team, another vendor or us. You own the document and the reasoning behind it.
Bring us a decision.
Tell us the question you are stuck on and we will scope an engagement that answers it, or tell you it does not need one.