A perpetual acquirer
with a data layer.

DataSolutions is raising $800K at a $15M FEA cap — priced below the $17.5M current estimated fair value ahead of the July 2026 acquisition re-rate. This is the early-access entry point.

$800K
Raise · $15M FEA Cap
Priced below $17.5M fair value · July 2026 re-rate ahead
$2.5M
Founder Capital at Risk
Invested ahead of this raise · full economic alignment
35+
Companies Integrated
16 years · same founder · same model · proven at scale
$45–50M
CY26 Valuation Target
AI conversion metrics quantified · comp set shifts to platform
ⓘ

Pre-close revenue is low by design — the JV model concentrates revenue inside partner companies while the data layer, acquisition system, and AI conversion infrastructure are built underneath them. The $15M FEA cap reflects a six-component value stack covering acquisition discipline, data infrastructure, AI conversion optionality, domain moat, and organic revenue capacity — each independently supportable. See the full valuation stack →

The Thesis

A perpetual acquirer. That changes everything.

The highest-performing compounders share one discipline: acquire niche businesses, hold indefinitely, operate with rigor, never sell. That model has produced sustained, outsized value creation across private markets.

DataSolutions runs the same playbook — perpetual acquirer, hold indefinitely, compound relentlessly — but with something no prior compounder has: a proprietary data unification layer that connects every company in the portfolio.

When a new business joins DataSolutions, its data gets unified through the MDM platform — clean, entity-resolved, and integrated with the portfolio. That unlocks three compounding advantages no traditional acquisition vehicle can access.

Cross-sell. Every portfolio company can sell into every other company’s customer base at near-zero incremental CAC — the data layer already knows who the customers are.

Bolt-on. Portfolio companies can integrate with each other as modular components, expanding their service offering without new sales cycles.

AI conversion. Clean, unified data is the prerequisite for AI automation of service delivery. Once it exists, human-led project revenue converts to AI-driven recurring revenue — and 15–20% EBITDA margins convert to 40–50%+ software-like economics.

Traditional compounders compound revenue. DataSolutions compounds revenue, margin category, and the intelligence layer that makes both grow faster with every acquisition added.

What Exists Today

This is not a roadmap. It is already running.

AI conversion is live inside Swift Insights and CentralApp today — before either acquisition has formally closed. This is not a projection. It is in operation.

The MDM Platform

Four enterprise systems unified: CRM, Tableau, Brevo, and website. ~9,000 contacts and ~4,000 companies under active management. Deterministic matching — definitive entity keys, not confidence scores. Originally deployed at 1.1M contacts and 900K companies. QuickBooks integration completing within 30 days.

140 Domains · 85% Global GDP

AI Conversion — Operating Now

Auto-wireframe dashboard generation: manual analytics converted to AI-driven output. AI-driven alerting: reactive human monitoring converted to proactive automated intelligence. Both live at Swift Insights and CentralApp today. Additional implementations in active development. Every implementation shifts project revenue toward recurring.

Live · Pre-Close

The Operating System

A fully encoded acquisition and conversion methodology spanning Culture, People, Process, and Technology. Every integration runs through the same repeatable system: validate, unify, convert, scale. No founder dependency. No tribal knowledge. The methodology survives any single person.

The Blueprint · $2M–$3M Standalone Value

Financials

Two moments, one business.

April pre-close actuals alongside May post-close projections — no adjustments, no pro forma smoothing. The right column shows what the business looks like the day the acquisitions formally close.

Close formalizes accounting, not economics. JV royalties are already flowing. The step-change on post-close reflects Swift and CentralApp consolidating into DataSolutions as full subsidiaries — revenue that exists today, recognized differently after close.

Pre-CloseApril Actuals
JV Partners
CompanyRevenueMarginEBITDARoyalty
Swift Insights$104,16020%$20,832$5,208
CentralApp$83,34020%$16,668$4,167
Efficus AI$20,840——$1,042
DataSolutions Revenue
SourceRevenueMarginEBITDA
JV Partners$10,417—$10,417
DS Clients$18,500—($51,500)
April Total$28,917-142%($41,083)
Post-CloseMay Anticipated · Excl. Pipeline
JV Partners
CompanyRevenueMarginEBITDARoyalty
Swift Insights————
CentralApp————
Efficus AI$20,840——$1,042
DataSolutions Revenue
SourceRevenueMarginEBITDA
JV Partners$1,042—$1,042
DS Clients$206,000—($14,008)
Monthly Total$207,042-6%($12,958)

Post-Close Annualized

$2.48M

EBITDA ($155K) · Margin -6.26%

Pre-conversion baseline

1st Target · $10M Rev

$985K

EBITDA · Margin 9.85%

2–3 companies consolidated

2nd Target · $25M Rev

$5.94M

EBITDA · Margin 23.74%

3–5 companies consolidated

Implied Valuations

Post-Close$20M
1st Target$45–50M
2nd Target$90–105M

The Model

Acquire. Unify. Convert. Compound.

Traditional rollups consolidate margin. DataSolutions converts the margin category entirely — from 15–20% EBITDA service businesses to 40–50%+ software-like economics. Every acquisition. Every time.

1.

Acquire

Service businesses at 15–20% EBITDA — validated through the JV filter first. No acquisition capital committed until fit is confirmed. 20% cash at close, 80% equity swap. Integration cost $80K–$200K per deal.

2.

Unify

Deploy the MDM platform. Fragmented systems collapse into one clean, entity-resolved data foundation. AI cannot execute on dirty data. This is the step that makes conversion possible.

3.

Convert

AI-driven delivery on clean data. Project work becomes recurring AI output. Target: 25% growth post-acquisition — 50% realized Year 1, 100% Year 2+. Margins move from services to software.

4.

Compound

Every acquisition enriches the data layer — making the next conversion faster and more accurate. More data → better AI → higher margins → more acquisitions. The flywheel accelerates with each turn.

StageEBITDA MarginRevenue CharacterImplied Multiple
At Acquisition (services)15–20%Mixed recurring / project3–5×
Post-MDM UnificationImprovingShifting toward recurring5–7×
Post-AI Conversion (target)40–50%+Predominantly recurring10–15×+

Market & Competition

Every service business. One data layer. No one else building this.

Traditional acquisition vehicles acquire and hold. DataSolutions acquires, unifies, cross-sells, bolt-ons, and converts — using a proprietary data layer that no competitor has and no incumbent can build without destroying their own business model.

The Flywheel

More Acquisitions

Every deal is validated through the JV filter before capital is committed.

5 JVs initiated. 2 cleanly exited before capital was at risk. 2 converting. 1 active. The filter works in both directions.

Richer Data Layer

Each acquisition adds data to the proprietary graph.

Making every subsequent AI implementation more accurate, and every conversion faster and cheaper than the last.

Better AI Conversion

Better data produces better AI output.

Each implementation gets encoded into the conversion methodology. The model improves with every company it runs through.

Higher Margins → More Acquisitions

40–50%+ EBITDA funds the next deal.

Cross-sell at near-zero incremental CAC across the portfolio. NRR floor: 105%. Formal tracking begins Q3 2026.

Why Incumbents Can't Compete

Informatica Cannot Build

Revenue model depends on implementation fees. Offering free MDM would structurally undermine their core economics.

Stibo / Riversand Cannot Build

Same structural constraint as Informatica. Legacy enterprise software players cannot disrupt their own revenue base.

AI-Native Point Solutions Missing Prereq

Cannot build the MDM prerequisite layer. Clean data is the input they require but cannot provide.

DataSolutions Full Stack

Deterministic MDM + AI conversion model + repeatable acquisition system + cross-sell infrastructure. Already operating.

Combined TAM

$500B+

~19% blended CAGR · Expands with every acquisition

Valuation

Six components. One entry point below all of them.

No single revenue multiple captures a business that acquires, unifies, cross-sells, and converts margin category simultaneously. The component stack below makes the value visible.

ComponentValue
Post-close services revenue — $2.07K monthly × 12 at 3.5× blended (~55% recurring)$8.7M
MDM platform + methodology — 140 domains, 1.1M contacts proven. $3M–$5M+ to rebuild from scratch. Owned outright. No licensed IP.$4M–$6M
The Blueprint (Operating System) — Encoded acquisition and AI conversion methodology across Culture, People, Process, Technology. Standalone value to any acquirer.$2M–$3M
Acquisition pipeline — 3 active JV conversations + 1 strategic distribution partner. Weighted at 50% (historical pass rate).$2M–$4M
Proprietary system & operator track record — 35-integration methodology encoded in The Blueprint. $2.5M personal capital at risk alongside institutional investors.$2M–$4M
AI conversion upside — 25% growth target already underway at Swift and CentralApp. Valued conservatively as embedded option.$1M–$3M
Total valuation range$19.2M–$28.2M

The Entry Advantage

The $15M FEA cap sits below the $17.5M current fair value estimate and below the conservative floor of the component range. Challenging any single component adjusts one input inside a range that still clears $15M across the remaining five.

Valuation Milestones

Now · Pre-Close
$15M cap
MDM live. AI conversion at two companies. $28,917/mo direct revenue. Cap priced below $17.5M fair value.
July 2026
$20M
Both acquisitions close. $2.48M+ annualized run rate consolidates. AI conversion formally inside DataSolutions. +33% re-rate from entry.
EOY 2026
$45–50M
First quantified AI conversion margin proof points. Comp set shifts from services rollup to AI-enabled platform. Third acquisition.
CY29 Base Case
$192M+
12–15 portfolio companies across multiple verticals. 40–50%+ EBITDA demonstrated at scale. Strategic exit, recap, or continued compounding.

Use of Capital

$800K. Fully allocated. Zero discretionary.

Capital is fully allocated with no discretionary component. The raise closes two acquisitions, funds runway through both, and deploys the AI conversion infrastructure that drives the post-close margin re-rate.

57%
~$456K · Acquisition Closes

$192K at CentralApp + $264K at Swift Insights — each representing 20% of total consideration. The remaining 80% is structured as equity swap, aligning acquired founders to post-close performance.

25%
~$200K · Operational Runway

Covers $100K/month operating burn through July close. The moment both acquisitions consolidate, the $2.48M annualized run rate inverts the burn equation entirely.

18%
~$144K · AI Conversion Infrastructure

Scales AI conversion tooling across Swift and CentralApp post-close. This is the operational mechanism behind the 25% post-acquisition growth target.

Exit Framework

Built to compound. Four credible exits.

DataSolutions is structured as a perpetual acquisition vehicle. Exit pathways are documented because capital requires optionality — not because the model is dependent on one.

1.

Cloud Platform Strategic

Snowflake, Databricks, Salesforce. Each needs a mid-market AI conversion layer they cannot build without cannibalizing existing customers. DataSolutions is the acquisition — not a product they could build themselves.

$1.15B–$1.54B implied · CY29

2.

Private Equity Mega-Rollup

By CY29, DataSolutions controls the unified data layer, AI conversion methodology, and customer relationships across dozens of mid-market companies in multiple verticals. That combination commands a meaningful platform premium.

Premium to $192M+ revenue · CY29

3.

Enterprise Software Strategic

SAP, Oracle, IBM are acquiring AI conversion capabilities they cannot build fast enough internally. The deterministic matching methodology and proven scale at 140 domains represent years of development — not replicable through R&D spend alone.

Strategic premium · Timeline flexible

4.

Continued Private Compounding

A perpetual acquisition vehicle is structurally built for this. Compound the data layer, grow the portfolio, and preserve full optionality — public markets, recapitalization, or continued private operation. No forced exit. No artificial timeline.

No forced exit · Full optionality

Team

Built for continuity. Authority is distributed by design.

Financial, legal, and operational authority are distributed across independent principals — by design, not contingency. The operative track record: one founder, the same model, 35+ integrations, 16 years.

MM
Michael Mesarch
Founder · CEO · 91% Owner

16 years overseeing integration of 35+ acquired companies. Architect of the AI conversion model, MDM platform, acquisition system, and JV framework. $2.5M of personal retirement capital invested alongside institutional investors.

Has executed this exact model — at scale — for more than a decade.

MC
Mikhail Christiansen
CAO · CEO Swift Insights · Designated Successor

Former Senior Analytics Consultant at Deloitte. Deloitte Applause Award recipient. Stood up Deloitte Ukraine’s analytics practice. LinkedIn Top Voice, 20,000+ followers. Primary operator of the AI conversion model today.

Active system access and authority today — continuity is structural, not contingent.

TC
Todd Cope
CFO, DataSolutions · CEO, CentralApp

Carnegie Mellon University. Multi-company CFO background. Dual role spanning corporate finance and portfolio company leadership. Direct oversight of DataSolutions financials and CentralApp AI conversion.

Financial discipline at holding company and portfolio level simultaneously.

NP
Nick Phelps
Lead Legal Strategist

Leads legal strategy across DataSolutions and the JV network. Supported by Torrey Pines Law Group and specialist IP counsel for patent scope assessment of the deterministic matching methodology.

IP protection, cap table, and JV legal structure — dedicated counsel.

JM
Joshua Michaell
Chief Resiliency Officer

20+ years organizational resilience experience. Helped establish One Medical’s mental health practice. Prior clients: Twitter, OpenAI, One Medical. Active, ongoing engagement — a structural operating component.

Organizational resilience is built into the architecture.

Principal Risks

Rated. Mitigated. Documented.

Every material risk is documented with a mitigation that is already in place or pre-funded by this raise. The downside floor is the operating business — not a projection.

Critical
Next Raise Timing

Current raise funds through July close. By Q3 2026, the company carries two closed acquisitions, a $2.48M annualized run rate, and the first quantified AI conversion proof points. Institutional outreach begins Q3 2026.

High
Dual Close Timing Risk

Both acquisitions are in active diligence at high to very high confidence. Two prior JVs exited cleanly before capital was at risk — the filter works in both directions. Under single-close downside, the component stack supports a $10M–$13M floor.

High
AI Conversion Slower Than Targeted

Conversion is already live at two companies. The 25% target is directional — any improvement above zero advances the margin profile and implied multiple. The floor is operating revenue, not projected revenue.

High
Burn Rate

$100K/month operating burn. This raise includes $200K direct runway through July. Post-close $2.48M annualized run rate inverts the equation — the business funds itself from close forward.

Medium
Revenue Mix Shift Slower Than Modeled

The valuation reflects the current ~55% recurring mix. AI conversion is the mechanism that shifts this mix — and it is already operating, not a future plan.

Medium
Integration Failure

The acquisition methodology is encoded and repeatable — not founder-dependent. Track record: 5 JVs initiated, 0 integration failures.

FAQ

Frequently asked questions.

The Platform

Is the MDM platform externally sellable, or is it an internal tool?

The MDM is not only a product — it is the operating layer that makes the AI conversion model possible. Originally built for a single enterprise client at scale (10–15 systems unified, 1.1M contacts, 900K companies), then extracted and rebuilt as a SaaS-ready, repeatable platform. Currently deployed internally and within the JV partner network. External MDM monetization is a CY27+ priority. The value is in what it enables: AI conversion of service businesses at scale, repeatedly, across every vertical that runs on business data.

What makes deterministic matching different from every other MDM tool?

Most MDM platforms resolve entities using confidence scores — probabilistic matches that still produce ambiguity at the record level. DataSolutions uses deterministic matching: every entity gets a definitive key, not a probability. That distinction is the prerequisite for AI conversion. Models trained on ambiguous data produce ambiguous outputs. Clean, deterministic data is what makes the margin expansion from 15–20% EBITDA to 40–50%+ achievable. No off-the-shelf tool replicates this.

What is the real recurring revenue percentage?

Approximately 55% recurring and 45% project-based across the combined CentralApp and Swift portfolio — pre-AI conversion. Formal NRR tracking begins Q3 2026, at which point that estimate becomes a measured figure. The model targets progressive conversion of project-based delivery into recurring AI-driven output — the mechanism behind the 25% post-acquisition growth target.

What AI conversion is actually live today — before any acquisition closes?

Two implementations are live inside Swift Insights and CentralApp today. First: auto-wireframe dashboard generation — manual analytics build work converted to AI-driven output. Second: AI-driven alerting — reactive human monitoring converted to proactive automated intelligence. Both are operating pre-close. The model is not being pitched. It is being operated.

What is the 140-domain portfolio and why does it matter?

DataSolutions holds 140 top-level domain variations of the “DataSolutions” brand, covering approximately 85% of global GDP. Any competitor attempting to build a competing platform faces a brand identity landscape where the most intuitive domain variations are already locked. Combined with the deterministic MDM methodology and the encoded operating system, the domain portfolio is the third layer of a three-part moat: technical, structural, and brand.

The Deal

Why does the $15M cap represent good value when pre-close revenue is only $28,917/month?

A pure revenue multiple on $28,917/month gives roughly $1M in implied value — and misses everything that makes this business. The $15M reflects six components: post-close revenue at 3.5× ($8.2M), MDM platform replacement cost ($4M–$6M), the Operating System ($2M–$3M), acquisition pipeline ($2M–$4M), proprietary system and operator track record ($2M–$4M), and embedded AI conversion option ($1M–$3M). Total range: $19.2M–$28.2M.

Why is the cap set below the current estimated fair value?

The $15M FEA cap is held deliberately below the $17.5M current estimated fair value to enable fast close. The July 2026 acquisitions are the first re-rating event — once Swift and CentralApp formally consolidate at $2.48M annualized run rate, the anticipated valuation moves to $20M. The cap was set to eliminate that optionality for the investor — not to signal uncertainty.

What is the acquisition structure — how does the 20/80 split work?

Each acquisition closes at 20% cash and 80% equity swap. The acquired founder receives DataSolutions equity in exchange for the majority of consideration — creating direct alignment on long-term AI conversion performance. This structure minimizes acquisition capital requirements and ensures acquired founders are economically incentivized to support the full AI conversion process. Integration cost per deal: $80K–$200K.

How is the $800K raise being used?

57% (~$456K) funds the acquisition closes — $192K at CentralApp and $264K at Swift Insights, each representing 20% of total consideration. 25% (~$200K) covers operational runway through the July closes at ~$100K/month burn. 18% (~$144K) funds AI conversion infrastructure scaling at Swift and CentralApp post-close. Zero discretionary. Every dollar is pre-allocated to a specific close or conversion milestone.

What does the forward raise schedule look like?

This $800K raise closes the two July acquisitions and funds through the first AI conversion proof points. The next institutional raise is planned for Q3 2026 — at which point the company carries two closed acquisitions, a $2.48M annualized run rate, and the first quantified AI conversion margin metrics. The $15M FEA cap is the early-access entry point.

The Model

What are the model’s locked assumptions?

Blended gross margin 60–65% expanding toward 40–50%+ EBITDA as AI conversion matures. Post-acquisition uplift 25% driven by AI conversion (50% realized Year 1, 100% Year 2+). NRR floor 105% — formal tracking begins Q3 2026. Organic growth 10% per year. Cross-sell attach rate 15%–50% (CY26 through CY29). Monthly operating burn ~$100K excluding acquisition capital.

What does the CY29 base case actually require?

The $192M+ CY29 base case assumes 12–15 portfolio companies acquired at an average $15M–$20M enterprise value, each contributing $10M–$20M in post-conversion annualized revenue. That pace — roughly 3–4 acquisitions per year — is consistent with the capital recycling math once the first two closes generate proof-of-concept AI conversion margin and unlock institutional outreach.

Are there two separate paths to scale, or just the acquisition engine?

Two engines — one active, one in reserve. The acquisition engine is the primary path today. The parallel organic engine — selling MDM plus services plus AI conversion directly to external clients without acquiring them — is built and ready. It has not been activated because the acquisition engine produces superior unit economics at this stage.

How does cross-sell actually work across the portfolio?

Every company that joins DataSolutions contributes its customer and company data to the unified MDM layer — deterministically matched, entity-resolved, and integrated with the rest of the portfolio. Cross-sell attach rate targets: 15% in CY26, scaling to 50% by CY29. CAC on cross-sell: near-zero, because the relationship already exists inside the data layer.

Risk & Diligence

What happens if only one of the two acquisitions closes in July?

Both are at high to very high confidence of close. Two prior JVs were exited cleanly before capital was committed — the filter works in both directions. Under the single-close downside scenario, the component stack still supports a $10M–$13M floor. The floor is operational, not theoretical.

How does the JV validation filter work?

Three stages. Stage 1: alignment assessment — leadership introductions, cultural evaluation, strategic fit, AI conversion readiness review. Stage 2: formal JV period (~6 months) — partner contributes 5% of revenue in exchange for MDM platform access, AI conversion tooling, deal room, shared services, and cross-referral network. Stage 3: conversion decision evaluated against documented criteria. Historical: 5 JVs initiated; 2 converting; 2 exited before capital was committed; 1 active.

What protects investors if something happens to Michael Mesarch?

These are structural protections — not contingency plans. Mikhail Christiansen is the designated operational successor with active system access and authority today. Our financial and investment authority is independent of the founder. The DataSolutions Operating System encodes the entire acquisition and AI conversion methodology — every process is repeatable without founder dependency. Formal succession protocols in preparation under Torrey Pines Law Group.

What is the burn rate and how long does this raise last?

Operating burn is ~$100K/month excluding acquisition capital. This raise includes ~$200K of direct runway — covering two months through the July closes. The moment both acquisitions consolidate, the $2.48M annualized run rate inverts the burn equation entirely. The business funds itself from close forward.

IP & Structural Protections

Who owns the MDM platform IP — and is it encumbered?

DataSolutions owns the MDM platform and deterministic matching methodology outright. No white-label components. No licensed IP. No encumbrances. Patent counsel is active through Torrey Pines Law Group, assessing the scope of patent protection for the deterministic matching methodology. The IP carries full standalone value to any acquirer without licensing tail risk.

What is The Blueprint and why does it carry standalone value?

The Blueprint is the encoded operating system for the AI conversion model — organized across Culture, People, Process, and Technology. It covers the full acquisition lifecycle: JV validation methodology, acquisition checklists, AI conversion implementation runbooks, cross-sell attribution protocols, MDM deployment standards, and deal room operating procedures. To any strategic acquirer, that methodology carries $2M–$3M in standalone value — independent of revenue.

What structural protections are built in for investors?

Several layers: (1) Founder has $2.5M of personal retirement capital invested. (2) Acquisition structure is 20% cash, 80% equity swap — acquired founders are long-term aligned. (3) Financial and investment authority is held independently by another party. (4) The JV validation filter means no acquisition capital is committed until fit is confirmed. (5) Cap table is maintained by Torrey Pines Law Group and available to qualified investors under NDA. (6) The Blueprint makes every process repeatable without any single person.

Capital & Structure

What is the cap table structure and who holds ownership?

Michael Mesarch holds 91% of DataSolutions Holding Company LLC. The remainder reflects early investor and team allocations. The full cap table is maintained by Torrey Pines Law Group and made available to qualified investors during formal diligence under NDA. This raise is structured as a Future Equity Agreement (FEA) with a $15M conversion cap.

What does the forward raise schedule look like?

This $800K raise is the pre-close entry round — structured to close fast before the July acquisitions re-rate the business. The next institutional raise is planned for Q3 2026. The Q3 2026 raise opens at a materially higher valuation. Entering today at $15M is the early-access position.

How is acquisition capital recycled as the portfolio grows?

The 20/80 acquisition structure minimizes cash outlay per deal. Post-close, each subsidiary operates at its own revenue base — the acquisition cost is recovered through operating cash flow. As AI conversion matures the margins from 15–20% toward 40–50%+, the incremental margin above baseline funds the next acquisition without requiring external capital for every deal. At scale, the flywheel is largely self-funding.

Is there a preferred return or hurdle structure for investors?

This raise is structured as a Future Equity Agreement — no preferred return, no hurdle, no liquidation preference above the conversion mechanics. Full economic terms are in the FEA document, available to qualified investors under NDA. Diligence materials including the cap table, financial model, and legal structure are available through Torrey Pines Law Group upon NDA execution. Contact devon.smith@datasolutions.com to initiate.

Confidential. For qualified prospective investors only. Does not constitute an offer to sell or solicitation to buy any security. All financial figures, valuations, and projections are forward-looking estimates based on current assumptions and are not guaranteed. Investment in early-stage private companies involves substantial risk, including the possible loss of principal. Cap table and diligence materials available upon NDA execution. DataSolutions Holding Company LLC — Suite 100, 901 N Market Street, Wilmington, DE 19801, USA.

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