01 Confidential client
Enterprise data integration platform
Twenty-plus enterprise systems that each held part of the truth, connected into governed data flows with reconciliation built in — across twelve business units and five countries.
Data integration · Analytics · AI automation
EthanCorp designs and runs enterprise data integration, analytics modernisation and AI-enabled workflow automation — for organisations whose data already exists, and whose real problem is that none of it connects.
Built as durable systems, not demos.
Worked with, in production
Platform and vendor technologies used in delivered work. Client names are withheld under confidentiality — the numbers throughout this site come from those engagements.
The problem
None of them are unusual. All of them are expensive, and all of them compound — because every workaround becomes something the next person has to work around.
ERP, MIS, CRM and finance each hold part of the picture. Joining them is a person with an export button.
Revenue, headcount, utilisation — each report defines them slightly differently, and nobody owns the definition.
A monthly pack assembled by hand, by one person, from files that arrive by email. It works until they are on leave.
A five-day close means leadership is steering on last month's data, which is a different job from steering on this week's.
Undocumented jobs written years ago, no tests, no lineage. Every schema change is a gamble taken at month-end.
The demo impressed everyone. Then nobody could say what it would cost to run, who reviews its output, or what happens when it is wrong.
What EthanCorp does
Foundations before front-ends. Connecting the systems and agreeing the definitions is unglamorous work, and it is what makes everything after it hold.
Connect ERP, MIS, CRM and cloud platforms into governed, observable data flows — and move data between them without a year of manual reconciliation.
Replace the monthly spreadsheet assembly line with dashboards leaders actually open — on definitions the business has agreed to, not definitions each report invented.
Design the models, pipelines and semantic layers underneath the reporting — so the next ten questions do not each need their own bespoke extract.
Automate the repetitive analytical work — document handling, report drafting, classification, retrieval — with APIs, Python, LLMs and orchestration, and a human review step where the decision matters.
Selected work
Three enterprise engagements and two systems built and run by EthanCorp. Client names are withheld where confidentiality applies; the figures are the ones already published on my professional profile.
01 Confidential client
Twenty-plus enterprise systems that each held part of the truth, connected into governed data flows with reconciliation built in — across twelve business units and five countries.
02 Confidential client
A five-day manual reporting cycle replaced with governed dashboards on standardised definitions — and the arguments about whose number was right replaced with one KPI dictionary.
03 Confidential client
A ten-step manual document workflow reduced to two guided steps, with an explicit human review gate — and the acceptance rate measured rather than assumed.
04 Live
A production RAG assistant answering iSAMS questions from a curated knowledge base, with an admin console, cost visibility and a feedback loop — free and open to the iSAMS community.
05 In development
A retrieval-grounded tour advisor for the Vietnamese market, built to test a two-layer NLU design: deterministic rules first, the language model only where the rules run out.
How I work
These are not values on a wall — they are the reasons a proposal gets narrowed, a launch gets delayed, or a request gets pushed back on.
Anything shipped should still be running, and still be maintainable, twelve months later. A demo that impresses a steering committee and then rots is a cost, not a delivery.
Data schemas, state tracking, clean contracts and written procedures come before the dashboard skin. A beautiful report on an ungoverned model is a faster way to be confidently wrong.
Automation removes the copy-paste, never the decision. Human-in-the-loop is a design feature, not an admission that the model is not good enough yet.
An over-engineered master plan that never goes live has delivered nothing. I would rather put a narrow, working v1 in front of real users and let their behaviour decide what v2 contains.
Token budgets, API rate limits, latency, schema drift, the failure point you will hit in week three — said up front. Buyers who were warned stay; buyers who were sold magic churn.
Technical depth
Tools are the supporting detail, not the argument. This is what the delivered systems actually run on.
Who you would be working with
EthanCorp is a one-person consultancy. There is no bench, no account manager and no junior team: the person who scopes the work is the person who builds it and the person who hands it over.
Twelve-plus years across enterprise data integration, BI delivery and analytics engineering — SAP and Microsoft estates, multi-country operations, and lately AI-enabled workflows with a human review step kept deliberately in place. Currently Application Integration & Data Analytics Lead for Asia at Cognita.
Built and running
Consulting is the primary work. These exist as evidence that the systems thinking survives contact with production.
Live
A production RAG assistant answering iSAMS questions from 17 curated guides, with an admin console, per-model cost visibility, a reviewed feedback loop and 218 automated tests. Free for the iSAMS community.
Read the case studyIn development
A productised version of the field-mapping work that eats the most hours in any migration: the tool proposes mappings with a confidence score and a stated reason, and a human accepts, edits or rejects every one. Early access has not opened yet.
See how it worksInsights
What tends to break, why, and the design decision that prevents it — written from delivery, without naming clients.
Integration projects rarely fail on the connector. They fail on identity, on late-arriving corrections, and on the fact that nobody agreed what a record means. Six failure modes, and the design decision that prevents each.
The dashboard is usually not the problem. It gets built against available fields instead of a named decision, ships without retiring the spreadsheet it replaced, and has no owner when a number looks wrong.
Tell me what is breaking and what you have already tried. If EthanCorp is not the right fit, I will say so and point you somewhere better.