SAP migration scope compiler for integrators that turns ECC evidence and workshop notes into fixed-fee S/4HANA plans.

1. The 2027 deadline and 35,000-company backlog make faster discovery throughput urgent rather than optional.
2. If only 8% of migrations already finish on time, buyers cannot keep absorbing scoping mistakes as a services problem.
3. A staffing crisis around SAP transformations creates budget for software that multiplies scarce principal architects.
4. Reported automation of scoping, analysis, and knowledge capture with up to 45% duration reduction makes this a workflow product category, not generic AI theater.
5. Early automotive traction and SAP-insider backing lower the adoption risk for a new vendor in a conservative ecosystem.

Catalyst. Qorelo's seed round, early automotive traction, and explicit data that 35,000 SAP customers face 2027 while only 8% finish on time show that discovery capacity is becoming a purchase driver now.

The product plugs into SAP ECC usage reports, custom-code inventories, transport histories, and workshop transcripts the moment a migration is being quoted or kicked off. It produces an auditable scope pack: processes touched, custom objects to retire versus rebuild, fit-gap decisions, a RICEFW backlog, effort estimates, and staffing assumptions. Senior architects review and edit each recommendation, while junior consultants inherit linked rationale rather than tribal knowledge trapped in meeting notes. Integrators also get variance tracking between scoped and delivered work, so the model learns which industries, plants, and process areas create change-order risk. Over time the company becomes the system of record for migration discovery and the benchmark dataset on how SAP transformations actually unfold.

What's different. Most ERP migration startups attack cutover, testing, or broad program management after the statement of work is already set. This company wins earlier, at the scoping moment where margin, staffing, and schedule are determined and where the talent bottleneck is most acute. By capturing decision rationale and actual variance across many migrations, it builds a proprietary corpus of how specific process patterns translate into effort, which generic copilots and labor-heavy integrators do not own.

Jobs to be done

flowchart LR
  Buyer[SAP practice lead] --> Pain[Scope and staffing bottlenecks]
  Pain --> Product[Migration scope compiler]
  Product --> Outcome[Faster bids and cleaner delivery]

Executive takeaways

• The near-term window is real: ASUG says 30% of respondents expect S/4HANA go-live in the next six to 24 months, Precisely says 59% are fully or partially live, and DSAG-linked reporting says only 27% of German-speaking users expect to finish by 2027 [7][8][12].
• Discovery is where margin leaks: ASUG says consulting fees are the main unexpected migration cost, Precisely says business process change, customizations, and defining requirements remain major barriers, and Natuvion found 30% of companies skipped analysis and 35% only discovered knowledge gaps during transformation [7][8][23].
• The competitive set is real but fragmented. smartShift is strongest on custom-code analysis, SNP and Natuvion on transformation path and data transition, Tricentis on impact analysis and testing, and Celonis on process intelligence. No incumbent clearly owns integrator-first fit-gap, backlog, estimate, and knowledge-handoff automation in one workflow [17][18][21][24][25][27][30][31].
• Willingness to pay exists because senior SAP talent is expensive and scarce: lead S/4HANA rates cluster around £900 to £1,150 per day in the UK and €800 to €1,200 per day in Germany, while overrun and schedule pressure make even modest discovery productivity gains financially meaningful [13][14][15].
• Adoption will hinge on trust and deployment posture, not raw model quality. GDPR, the EU AI Act, and UK ICO guidance all push toward human oversight, traceability, and controlled data handling, while Qorelo already markets private-cloud, BTP, and on-prem deployment with German data residency [4][33][34][35][36].

Market definition

Software that turns ECC usage, custom code, fit-gap workshop inputs, and SAP Best Practices mapping into auditable S/4HANA scope packs for integrators and enterprise CoEs. It sits between custom-code analysis, selective-data-transition factories, testing and impact-analysis suites, and process mining: upstream of build, test, and cutover, but downstream of generic AI assistants [2][3][17][21][22][24][25][27][30][31].

Customer and buyer

Primary users are practice leads, principal architects, and PMO or CoE teams running brownfield discovery. Qorelo explicitly targets consultancies and enterprises, naming solution architects, process owners, functional leads, PMO, and SAP CoE teams as users, while ASUG and Precisely show consultant and partner capacity tightening as more customers move toward go-live [5][6][7][8]. The economic buyer is usually the SAP practice leader, VP Delivery, or CIO who owns bid margin, staffing, and schedule risk [5][6].

Buying triggers

• A backlog of RFPs or go-lives lands inside the next six to 24 months, so discovery throughput becomes the gating resource. [7][8][9][12]
• Consulting fees, process complexity, or customizations push discovery and migration budgets beyond plan. [7][8][10][23]
• Custom code and fit-gap ambiguity remain unresolved because only 38% of organizations report a detailed custom-code migration strategy. [16][18][19]

Willingness to pay

The budget line is not AI experimentation; it is architect leverage and overrun avoidance. ASUG says consulting fees are the main source of unexpected migration cost, while public rate data puts senior S/4HANA leads in the high hundreds per day in both the UK and Germany. If a scope compiler saves even a few architect-weeks per fixed-fee discovery or prevents one under-scoped workstream, mid-five-figure per-project software spend is easy to justify. [7][13][14][15]

Category dynamics

Growth signal 59% of companies are fully or partially live on S/4HANA in 2026, up 13 percentage points from 2024

Validation signals

• Qorelo raised seed five months after launch and says Mercedes-Benz or a leading German automotive enterprise is already live, suggesting the wedge resonates with demanding buyers.
• smartShift says 95% of surveyed SAP users run custom ABAP and has SAP Store distribution plus 3,300 transformed systems and 3.5 billion lines of code, proving adjacent budget exists.
• SNP and Wipro, plus SAP and Tricentis, show that ecosystem players already integrate third-party modernization tooling into mainstream delivery motions.
• Natuvion found 32% of companies would involve external consultancy earlier next time, pointing directly at demand for prep-stage tooling and analysis discipline.

Regulatory & technical constraints

• Any AI recommendation affecting process fit, controls, or staffing assumptions needs logging, documentation, human oversight, and audit trails.
• ERP extracts and workshop transcripts can include personal or regulated operational data, so buyers will prefer customer-controlled deployment and a clear GDPR posture.
• Scope quality depends on deep code, dependency, and context ingestion; shallow copilots without system-analysis inputs will underperform.

Competition clusters by layer. Qorelo is the closest direct analogue, already promising fit-gap, documentation, and migration guidance for SAP teams [1][2][3][5][6]. smartShift proves buyers will pay for governed automation around custom code and Clean Core, but its center of gravity is code lifecycle management [17][18][19]. SNP and Natuvion lead with migration-path, data-transition, and near-zero-downtime factories rather than integrator-first scope-pack generation [21][22][24][25][26]. Tricentis owns impact analysis and testing confidence later in the lifecycle, while Celonis owns process intelligence and modernization visibility across systems [27][28][29][30][31]. The biggest substitute remains human: senior architects, offshore analysts, Excel scope sheets, and SI discovery workshops [6][7][13][23].

Why incumbents do not win by default

• SAP ecosystem rails. SAP-adjacent rails shape procurement and deployment through SAP Store, Cloud ALM, BTP, and private-cloud hosting, but they do not solve consultant-specific scope synthesis or fixed-fee discovery economics by default.
• Custom code automation vendors. smartShift is credible where the bottleneck is ABAP analysis and Clean Core remediation, but the proposed startup wins only if it expands beyond code to workshop reasoning, process scoping, staffing assumptions, and handoff knowledge.
• Transformation factories. Natuvion and SNP are strong when buyers want a proven migration path, selective data transition, or partner-enabled factory model, yet both center on transformation execution path and data movement rather than AI-first pre-SOW scope authoring.
• Testing and impact-analysis suites. Tricentis has powerful SAP release assurance and SAP-backed distribution, but that advantage sits later, after key fit-gap and backlog decisions are already made.
• Process intelligence platforms. Celonis can replace manual process-mapping workshops and provide a digital twin, but it stops short of turning discovery artifacts into an auditable RICEFW backlog and commercial estimate by default.

SAP Scope Compiler sells to 20- to 150-person SAP integrators in DACH and the UK that are being squeezed by the S/4HANA migration backlog and a shortage of principal architects. The product ingests ECC usage reports, custom-code inventories, transport history, and workshop transcripts to generate an auditable scope pack before the statement of work is signed. The immediate buyer is the SAP practice leader or VP Delivery whose margin is exposed when fixed-fee bids are under-scoped and junior teams inherit incomplete workshop context. The beachhead is brownfield ECC-to-S/4HANA programs for automotive suppliers and industrial manufacturers because those programs combine deadline pressure, heavy customization, and expensive architect day rates. Go to market starts with paid design-partner pilots priced per scoped migration and converts successful pilots into annual practice subscriptions tied to analyzed program volume. The company wins if it can prove faster discovery cycles, lower architect hours, and lower scoped-versus-delivered variance while keeping every recommendation traceable and human approved. The main disconfirming risks are that regional SIs may prefer white-labeled services to direct software spend, that early project data is too messy to support accurate estimates, and that security review slows pre-SOW adoption. Market sizing in the inputs is estimate-based rather than disclosed by buyers, so the first 12 months must validate direct budget ownership, deployment posture, and pilot-to-production conversion before the company scales hiring.

Problem

• Fixed-fee SAP discovery is bottlenecked by scarce principal architects, which stretches scoping cycles, weakens statement-of-work accuracy, and traps project rationale in spreadsheets and workshop notes.
• Existing SAP tooling addresses code analysis, data transition, testing, or process mining separately, but regional integrators still lack one workflow that turns cross-artifact evidence into a defensible fit-gap backlog, estimate, and handoff pack.

Solution

• Ingest common ECC usage, custom-code, transport, and workshop artifacts and generate auditable fit-gap decisions, a RICEFW backlog, effort estimates, and staffing assumptions for architect review.
• Track scoped-versus-delivered variance across projects so integrators can benchmark risk, improve estimates, and let junior consultants execute from linked rationale instead of tribal knowledge.

Why we win

• The wedge sits at the pre-SOW scoping moment where margin is set, architect scarcity is most painful, and adjacent incumbents have the weakest end-to-end workflow coverage.
• Each production scope pack creates proprietary data on accepted decisions and downstream variance, improving estimate quality and making repeat migration practices harder to switch away from.

Milestones

flowchart LR
  Wedge[Brownfield SI wedge] --> MVP[Auditable scope compiler]
  MVP --> Proof[Faster scope and lower variance]
  Proof --> Expansion[Annual practice licenses and CoE rollout]
  Expansion --> Moat[Benchmark dataset and partner distribution]

Founding team

Experiment roadmap

Risk assessment

What must be true

• At least 5 of 10 target DACH or UK boutiques will sponsor a paid pilot from delivery-margin or practice budget instead of demanding bundled consulting first.
• In live pilots, more than 70% of generated fit-gap and backlog recommendations will be accepted with only minor architect edits.
• The product will cut discovery cycle time by at least 30% and principal-architect hours by at least 25% without increasing first-90-day delivery variance.
• Private-cloud, BTP, or on-prem deployment plus DPA review will clear customer security review within 8 weeks for automotive or industrial buyers.
• At least half of paid pilots will convert into annual subscriptions because the tool proves margin protection and knowledge retention, not just faster document creation.

Open diligence questions

• Who actually owns budget for pre-SOW discovery tooling inside a 50- to 200-person SAP boutique?
• Which artifact types drive architect trust most strongly in the first scope pack?
• How often is enough ECC evidence available before the statement of work is finalized?
• Which deployment posture clears security review fastest in DACH automotive and industrial accounts?
• Will design partners accept direct software pricing, or insist on white-label packaging inside billable services?

Model sanity

• Revenue engine. Base-case revenue comes from reaching 20 paying practices or CoEs by Q4Y3 while moving retained accounts from $117K land ACV toward $138K expanded ACV.
• Must go right. The company has to keep pilot-to-annual conversion above 50% and make the M16 GTM hire productive without breaking the trust-heavy implementation motion.
• Model breaks if. If security review or data quality pushes the sales cycle toward 8 months, downside cash falls to about $279K and full-year Y3 EBITDA stays deeply negative.
• Next-round proof. A credible next round is earned by exiting Y2 with about 11 paying accounts, production benchmark dashboards, and one enterprise CoE rollout proving the wedge expands beyond design partners.

Scenarios

Sensitivity

flowchart LR
  TargetAccounts --> PaidPilots
  PaidPilots --> AnnualSubscriptions
  AnnualSubscriptions --> ExpansionModules
  AnnualSubscriptions --> GrossProfit
  ExpansionModules --> GrossProfit
  GrossProfit --> EBITDA
  EBITDA --> Cash

Flags: Full-year Y3 EBITDA remains slightly negative even though Q4Y3 turns positive, so the business still needs operating discipline before a larger scale-up. · The base case assumes founder-led and partner-led selling can carry the company to 20 accounts before adding a dedicated AE, which may prove optimistic if referrals underperform. · Year-end ARR runs modestly above the researched $2.5M SOM shorthand because the model assumes 40% second-practice expansion and a few premium pilot months still in the mix. · Cash approximates EBITDA and excludes working-capital timing, VAT or tax timing, and capex, so treasury precision is lower than a board model.

• Channel conflict. Large integrators or SAP ecosystem partners may resist a product that exposes weak scoping discipline or compresses billable discovery work. Mitigation: Start with regional integrators whose margins depend on faster discovery, and package outputs so partners can white-label them into their own delivery motions.
• Estimate trust. Buyers will not sign multi-million SOWs from black-box AI recommendations. Mitigation: Make every recommendation traceable to source artifacts, require architect approval, and show forecast-versus-actual variance over time.
• Messy source data. Legacy SAP estates may not provide clean usage, custom-code, or workshop data in the format the model expects. Mitigation: Begin with opinionated ingestion for the most common ECC artifacts and pair the product with guided workshop capture to fill missing context.