Meet the Leader

Kyle Castor on value creation in basis points

Kyle Castor, Founder & Principal Architect  •  61 seconds  •  Captions  •  AI-rendered presenter from the studio portrait

Transcript

00:00To private equity sponsors and operating partners here in Las Vegas: your post-acquisition value creation shouldn't be trapped in forty-page slide decks.

00:11At DataOngoing, we measure our work strictly in basis points of EBITDA. Two hours of executive input returns hundreds of automated hours, proven in our 100x time ledger.

00:24First, a 48 to 72-hour AI technology diligence read to price technical debt before wiring capital. Second, compressing your 21-day multi-entity close down to 3. Third, automated floor-to-ledger data ingestion straight into NetSuite.

00:44We ship working code in 14-day sprints. If it does not run in production, the milestone is not billed. Visit DataOngoing.ai to schedule a private advisory session.

  1. How we work →
  2. Read the results ledger →
  3. The productized offers →
  4. The Basis-Point Sprint →

Every figure in the brief is published on this site with its source class; the chapter links go to those pages.

Home / How We Work
Delivery velocity

The 100X Speed Advantage: 10-50x Faster Delivery, 100x on Your Time

DataOngoing delivers AI automation, diligence and consolidation work 10 to 50 times faster than conventional consulting because we run AI-driven static analysis against the actual codebase and metadata instead of weeks of stakeholder interviews, staff every engagement with principal architects only, and ship working code in fixed-price two-week sprints. Speed is what makes 100x on your time possible: a few hours of operating-partner input returns hundreds of hours of automated work, and every row of that claim is published in the results ledger.

The three rules of the 100X Speed Advantage

If an enterprise consulting firm cannot show you working code running in your sandbox within fourteen days of signing, you are not paying for engineering; you are subsidizing overhead. The traditional model sells a $250,000 to $400,000 discovery phase, staffs it with junior analysts, runs eighty hours of interviews, and delivers a deck whose last slide quotes Phase 2. Prolonged ambiguity is its revenue driver. We engineered the opposite.

  1. No junior staff billing hours. You work directly with principal architects who have spent 13 years writing SuiteScript and optimizing high-volume ledgers. Nobody learns your business on your invoice.
  2. Diagnostic automation over manual interviews. Instead of four weeks of subjective interviews, automated diagnostics run directly against your transaction, line and system-note records. Within 48 hours the scan has pinpointed margin leakage, governor-limit bottlenecks, unallocated clearing balances and stalled orders.
  3. Fixed-price two-week production sprints. Every sprint has a defined deliverable: a working Map/Reduce pipeline, a Suitelet, an integrated pricing floor, an agent with validation rules. If the code does not run in production, you do not pay the milestone.

The result for an operating partner is measured in two currencies. In calendar time, delivery is 10-50x faster than the conventional baseline (table below). In executive time, a few hours of input returns hundreds of hours of automated work a year, which is the results ledger.

The benchmark, with denominators

A speed claim without a denominator is marketing. Here is ours, stated against the conventional baseline for each workstream so it can be checked against any competing proposal you hold.

WorkstreamConventional baselineDataOngoingMultiple
Technology diligence report4-6 weeks48-72 hours14-21x
Source-system API integration6-12 weeksSame or next day30-60x
Script and permission inventory2-3 weeks of manual reviewAutomated static analysis, hours40x+
Multi-entity period close21 business days3 business days7x
Shop-floor device integration3-6 months via WMS project2-3 week sprint6-12x

Why the difference is this large

  1. The system already contains the answer. Script deployments, permission tables, integration endpoints and posting history are facts sitting in the instance. Conventional diligence rediscovers them by asking people. We read them.
  2. Static analysis scales in a way interviews do not. Parsing every customization in a target instance takes compute, not calendar. Reviewing forty scripts by hand takes two weeks; parsing them takes minutes, and the human hours go into interpreting what was found.
  3. Most middleware is unnecessary. A large share of integration timelines is spent configuring a platform whose purpose is to abstract an API that is already straightforward. Writing directly against the native API removes both the timeline and the recurring subscription.
  4. Fixed scope removes the discovery tax. Open-ended time-and-materials billing rewards long discovery phases. We quote fixed deliverables, which means discovery has to be efficient for us too.

What does not get faster

Speed is a property of the analysis, not of the governance. Changes are still isolated, compared against committed scope, checked for net financial impact, permission-enforced and routed for approval before anything touches a system of record. We build the governed structure first. That part is deliberate, and it is why the fast part is safe.

Engagement model

Frequently asked questions

Is 10-50x a marketing number?

It is the range across the workstreams in the table above, from 7x on a period close to 60x on a straightforward integration. We publish the baselines so the claim can be checked rather than taken on faith.

How is 10-50x different from the 100x claim?

10-50x is calendar time: how much faster a deliverable lands against the conventional baseline. 100x is executive time: hours an operating partner or CFO puts in against hours of work returned over twelve months. Both are published with denominators. The fee guarantee is a third number, 10x, and it is stated separately so the three are never confused.

What is the conventional baseline based on?

Published diligence and integration timelines from established advisory practices, and the competing proposals our clients have shown us during selection. Where a specific engagement differs, the honest comparison is against the proposal in front of you.

Does moving this fast increase risk?

The risk in ERP work comes from ungoverned change, not from short timelines. Long projects with weak change control fail more often than short ones with strong change control. We front-load the governance and then move.

Talk to the architect, not a salesperson

HelpAirs technology for NetSuite: the five roles a company pays for, delivered as one supervised AI service at a modeled 20-80% lower cost, with the existing team repurposed rather than replaced, and every outcome published in the results ledger with its source class.

Scope a Two-Week Basis-Point Sprint   Read the results ledger

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