How to evaluate a business platform, and what a stack of disconnected tools actually costs. Written for the person who has to decide.
9 min read
A consulting engagement crosses seven handovers between first conversation and paid invoice, and most firms run each one in a different tool. Here is what one system has to cover, the questions to ask any vendor, and the mistakes firms make when they consolidate.
A client portal can end the weekly status email, or it can show a client your internal notes. What a consultancy’s clients should see, what they should not, the grey areas to decide per engagement, and the questions to ask before you choose a portal.
The integration tax calculator’s own model, run at three team sizes with its default assumptions. Every line, every total and every input is stated, so each number can be reproduced in the calculator, along with why the share that is not licences falls as a team grows but never drops below half.
A CRM runs the work before the signature, PSA runs the work after it, and an all-in-one platform tries to hold both on one set of records. What each one does, where each fits by firm size and complexity, what the seams between them cost, and when a dedicated PSA is the right answer.
A sales CRM is built for transactions that end at “closed won”. Consulting runs on engagements that start there. What a consultancy should look for in a CRM, a demo script that tests the handover from sale to delivery, and the questions to put to any vendor.
The AI demo is not the risk. The permission model underneath it is, and it is the thing that decides whether the feature can ever leave the pilot group. Eight questions, product-neutral, with the answer you want to hear for each.
Licences are the smallest line. Here is an open, assumption-by-assumption model of what it costs to run sales, support, docs, projects and finance in five separate systems — including the line that has only existed since AI arrived.
Every vendor now says their platform is AI-native. Seven questions separate the ones where that is an architectural fact from the ones where it is a feature line — each with a concrete answer you can ask for in a single demo.
Why an AI-native platform has to be designed that way from the foundation: one data model, one context surface, one set of guarantees.
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For consulting firms: winning engagements, delivering them on budget and getting paid, and what the software underneath has to do at each step.
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One platform for sales, projects, support, docs and financials, with the AI underneath rather than bolted on. Join the waitlist to be among the first to use it.
