Konfidas, a Tel Aviv cybersecurity and crisis-management consultancy, had chosen Salesforce for its quoting power. An expensive, frustrating run pushed them to leave and find a CRM they could actually operate. Here's how the migration came together.
TL;DR
The challenge
Konfidas came to us after a long and costly run on Salesforce. They had chosen it originally for its quoting capability, but the experience had been expensive and frustrating, and poor service was what finally pushed them to leave. Their business runs on unusually complex pricing: a large service catalog, dynamic line items, license-based tiers, hourly banks, and region-specific partner pricing — all held together in a sprawling manual spreadsheet. Quoting was the pain that mattered most, and recurring customer reports were consuming heavy manual effort alongside it.
They needed a CRM they could actually operate, a single source of truth for pricing and quoting, and they needed it stood up quickly so they could get back to selling.
What we built
We started with the data. We migrated Konfidas's core Salesforce objects into HubSpot in the opening weeks of the engagement: 978 companies, 808 deals, 63 line items, and a 1,333-record contact export, with 732 contacts created and a follow-up pass to de-duplicate and update the rest. The migration was complete before the quoting-tool kickoff at the end of September 2024.
On that clean base we rebuilt the revenue engine. We configured an eight-stage sales pipeline with mandatory fields gating each stage, mapped custom properties across contacts, companies, and deals, and built the customer journey: lifecycle-stage logic, MQL and SQL definitions, lead-source mapping, routing, deal ownership, and a leads-conversion dashboard.
For quoting, we ran a structured evaluation of five CPQ platforms against Konfidas's real need for flexible, dynamic line items, and selected DealHub as the best fit. We implemented it jointly with the DealHub team, reaching go-live for their consulting line in about seven weeks, then extended it into contract-renewal automation.
We also put real work into data quality — consolidating duplicated contract fields on the company record and standardizing subscription and billing fields so the numbers were reliable. In HubSpot, we built customer-satisfaction surveys with service-line-aware questions and a follow-up automation that flags a low score, creates a task, and routes the response to leadership.
The results
Konfidas's full Salesforce dataset moved into HubSpot in the opening weeks of the project — the core company, deal, line-item, and contact imports ran inside a single week and were complete before the CPQ kickoff.
The quoting platform reached go-live for the consulting line in about seven weeks, using 43 of a 70-hour services package, before being extended into renewals. Around it, Konfidas gained working lifecycle automation, lead routing, a conversion dashboard, and a live customer-feedback loop. The client's read on the work was positive throughout, with the CEO describing the team's answers as precise and the value delivered as high.
"ScaleOps were precise and professional from the start. Their onboarding was textbook, and as a company that delivers service ourselves, we had something to learn from them. We were very happy with the work."
— Ram Levi, Founder and CEO, Konfidas
The lasting value: an AI-ready foundation
Konfidas left Salesforce and now runs its CRM and its quoting on a HubSpot foundation, with DealHub integrated as the CPQ. The single source of truth for pricing they set as the goal is the shape of what they operate on today. The quoting process that a legacy platform had made painful — and that off-the-shelf document tools could not support — now runs on a fit-for-purpose CPQ wired into the CRM, so a quote and the deal it belongs to live in one place.
The most durable value is the foundation the migration left behind. Contacts, companies, deals, and line items were imported with de-duplication; custom properties were mapped per object; duplicate and inconsistent fields were consolidated and standardized; the pipeline was gated by mandatory fields; lifecycle stages and lead sources were defined; and the product catalog was structured for segmentation by service line.
That is what an AI-ready environment looks like. Because the object model is clean, consistent, and mapped to lifecycle and service-line segmentation, AI-driven reporting, segmentation, and enrichment can run against stable, well-defined fields rather than the tangle of a legacy export. The migration was not only a change of platform — it was the point at which Konfidas's data became a reliable base for whatever they build on top of it next, including AI.
Thinking about a migration of your own?
ScaleOps helps revenue teams move to HubSpot and get more out of it, from data migration and pipeline design to CPQ and customer-success automation.
Questions we get asked about this
How long does a Salesforce to HubSpot migration take?
Konfidas’s core company, deal, line-item and contact imports ran inside a single week and the full dataset was complete before the CPQ kickoff. Timelines depend on data volume and how much cleanup the legacy export needs, but the migration itself is usually measured in weeks rather than months.
Can HubSpot handle complex quoting and pricing?
HubSpot’s native quoting covers straightforward cases, but a large service catalog with dynamic line items, license tiers, hourly banks and region-specific partner pricing needs a dedicated CPQ. For Konfidas we evaluated five platforms and implemented DealHub alongside HubSpot, so the quote and the deal it belongs to live in one place.
What makes CRM data AI-ready?
A clean, consistent object model with properties mapped per object, duplicates consolidated, pipeline stages gated by mandatory fields, and lifecycle stages and lead sources actually defined. AI-driven reporting and segmentation can then run against stable fields rather than guessing at a legacy export.
