Your data is an asset. We help you value and monetise it.

Your data is worth
trillions.
It just is not valued yet.

Recognised on your balance sheet. Realised in the market.

85% of enterprise data sits off the balance sheet, unrecognised, unpriced, and unmonetised. Data Equity is the platform that closes that gap: discover, value, and turn your latent information assets into a new revenue stream, compliantly and at board-level credibility.

8bn
Global demand for commercial data, growing to USD 19bn by 2033
85%
of enterprise data assets sit off-balance-sheet, unrecognised and unrealised
15x
premium well-governed datasets command over ungoverned equivalents
98%
reproducibility, the standard every DataVault score is held to by design
The asset you already own

Your data is in demand.
We help you realise its value.

"You already recognise brand equity and IP on your balance sheet. Your data belongs there too, with a value you can defend."

Your organisation generates data every day, transactions, behaviours, signals, and records, that other industries urgently need. Insurers need healthcare patterns. Logistics firms need retail flows. AI developers need proprietary training sets. The buyers exist. The demand is real and growing fast. What has never existed is the infrastructure to value, price, and transact this data with confidence.

Inorganic revenue from assets you already own
No new capital investment required. Your data is already there, unpriced and unlicensed. We provide the methodology and marketplace to monetise it safely and compliantly.
Compliant by architecture, not by policy
GDPR, PDPL, CCPA: raw data never leaves your environment. The On-Premise Discovery Agent transmits only a metadata payload. Data Equity is never a data controller, processor, or custodian.
A signed credential, not a consultant's opinion
SHA-256 cryptographically signed. Immutable audit trail. Every sub-score traces to a named, logged input. Buyers rely on the DataVault report in lieu of their own due diligence.
Enterprise balance sheet, before and after DataVault
Today, without DataVault
Property and equipment$240M
Patents and IP$85M
Brand equity$60M
Data assetsNot recognised
Goodwill (bundled)$120M
With DataVault, IAS 38 compliant
Property and equipment$240M
Patents and IP$85M
Brand equity$60M
Data assets (DES certified)$35–52M
Goodwill (separated)$85M
The DataVault credential is the first methodology purpose-built to satisfy IFRS IAS 38, making data a separable, identifiable, and reliably measurable intangible asset on your balance sheet.
Why now

Three reasons your data is worth more than ever.

Buyer demand, new regulation, and M&A scrutiny have converged. Together they make the data you already hold more valuable, and easier to prove, than ever before.

01
Demand shift
The buyer has budget, but no price anchor
AI developers and data brokers are paying 10–100x previous rates for proprietary, domain-specific datasets. Deals are live and urgent. But sellers cannot justify or defend any number. Every transaction underprices or stalls.
DataVault gives you a defensible valuation buyers will trust.
02
Regulatory tailwind
Compliance is done. Valuation is not.
UAE PDPL, EU AI Act, and DORA now require enterprises to document and govern their data assets. That documentation exists inside most organisations today. What it does not produce is a financial value. The compliance cost is sunk.
DataVault converts existing documentation into a financial instrument.
03
M&A pressure
Data is on the balance sheet in name only
Acquirers now explicitly demand data asset valuations in deal processes. Targets cannot produce one. Acquirers cannot audit one. Data is written to zero by default, destroying value on both sides of every deal.
DataVault converts the gap into a credentialed, auditable report in 2–4 weeks.
End-to-end pipeline

Discover. Value. Monetise.

Nine stages, five AI-augmented, coordinated by a purpose-built Claude agent network via Amazon Bedrock.

Discover
AI
01
Data Discovery
Automated crawl across enterprise systems, data lakes, warehouses and external feeds. Full registry with location, format, owner and lineage. Claude via Amazon Bedrock.
AI
02
Ingestion and Profiling
Schema analysis, PII detection, statistical profiling and lineage mapping at source. Machine-readable fingerprint per dataset. Deterministic Python and NLP classifier.
03
Governance Tagging
Sensitivity classification, data sovereignty, consent and licensing attributes. Mandatory GDPR, PDPL and CCPA compliance gate before any valuation step proceeds.
Value
AI
04
Dimension Scoring
12 AI-powered dimensions: quality, rarity, accuracy, recency and commercial relevance. OPA Rego policies, deterministic, auditable, reproducible to 98%. Sector-calibrated model weights.
AI
05
Benchmark Comparison
Sector-relative positioning via retrieval-augmented model over the Data Equity live transaction database. Percentile ranking with confidence interval per dimension.
06
Data Equity Score (DES)
SHA-256 signed credential. Certified, auditable, portable across buyers and platforms. The credit rating for the data economy.
Monetise
AI
07
Marketplace Listing
AI buyer-matching, real-time demand sensing and automated price discovery. DE InfoBot surfaces the right buyers across the exchange. Automated listing optimisation.
08
API Distribution
Secure, metered REST and streaming APIs. Granular entitlement and usage controls enforced at the gateway. Configurable rate limits and access windows.
09
Revenue and Audit Trail
Automated billing, real-time usage analytics and immutable transaction records. Per-buyer revenue attribution with full provenance documentation.
The outcome
From raw data to investable Data Equity
A signed DataVault report in 2–4 weeks, the credential that converts your information assets into a board-level financial instrument, a balance sheet entry, and a new revenue stream.
2–4 weeks delivery
98% reproducible
SHA-256 signed
IAS 38 compliant
Data never leaves your environment
The agent network

Meet the agents behind every valuation.

A purpose-built Claude agent network on Amazon Bedrock runs the pipeline end to end: each agent owns one job, every output is logged, auditable and reproducible.

Discovery Agent

Crawls enterprise systems, lakes, warehouses and external feeds to build a full data registry: on-premise, raw data never leaves your network.

Profiling Agent

Schema analysis, PII detection and statistical profiling at source; a machine-readable fingerprint per dataset.

Governance Agent

Applies sensitivity, sovereignty, consent and licensing tags; enforces the GDPR, PDPL and CCPA gate before any valuation.

Valuation Agent

Scores 12 commercial dimensions via deterministic OPA Rego policies, reproducible to 98%, producing the Data Equity Score (DES).

Benchmark Agent

Positions each dataset against the live transaction database with percentile ranking and confidence intervals.

Matching Agent (DE InfoBot)

Surfaces the right buyers across the exchange with real-time demand sensing and automated price discovery.

Audit Agent

Logs every rule and input to an immutable, SHA-256 signed audit trail for M&A, regulatory and IAS 38 verification.

Safe for every industry

Your data stays yours.
Only its value moves.

The biggest objection to data monetisation is GDPR, privacy, and cyber risk. We have built the architecture that removes all three barriers, and produces a credential that proves it.

✕
Raw data never leaves your network
The On-Premise Discovery Agent runs entirely inside your infrastructure. It transmits only a structured metadata JSON payload: schema, statistics, PII flags. No records, no rows, no personal data ever crosses the boundary.
✓
GDPR, PDPL and CCPA compliant by architecture
Data Equity is never a data controller, processor, or custodian. This is enforced by system architecture, not by policy or contractual assurance alone. We produce documentation that satisfies GDPR Article 30 record-keeping requirements.
✓
Cross-industry monetisation, safe with the right derivative
A bank's SME credit patterns can safely inform insurance underwriting. A hospital's treatment flows can inform pharmaceutical research. Pseudonymisation, aggregation, and synthetic generation unlock cross-industry value while removing the GDPR blocker. We model the raw and derivative track and show you the net revenue of each.
✓
Every decision is auditable and traceable
OPA Rego policies power all scoring rules. Every rule that fires is logged. Every sub-score traces to a specific named field. The SHA-256 signed report and immutable audit trail satisfy M&A due diligence, regulatory scrutiny, and IAS 38 verifiability requirements.
IAS 38 proof chain: how DataVault passes the standard
1
Asset Ingestion
Field-level profile via OPA. Schema, distributions, null rates, PII flags, all observable and logged at ingest.
2
OPA Rego Policies
Deterministic scoring rules. Same inputs always produce the same output. Independent parties can replay the full computation from the audit log.
3
Five-Lens DES
Weighted composite score. Each sub-score supports IAS 38 separability, meaning the asset is identifiable apart from the business as a going concern.
4
OPA Audit Log
Full input trace. Every rule that fired. Every input that was used. Seven-year retention for regulatory and M&A purposes.
5
SHA-256 Credential
Cryptographically signed at issuance. Cannot be altered post-issue. Any third party can verify. Satisfies IAS 38 independent verifiability.
✅
The DataVault credential is the first data valuation methodology structured to satisfy IAS 38: reliable, verifiable, traceable, and separable by design.
Who we serve

Designed for the C-suite.
Built for the board room.

Every function of your leadership team has a direct stake in your data assets. We speak to all three.

Chief Financial Officer
Put data on the balance sheet. Unlock new revenue.

Your data assets are generating zero balance sheet value today. Under IAS 38 (IFRS), they can be recognised as intangible assets once reliably measured. The DataVault report is that instrument, certified, auditable, and defensible in an M&A process or audit.

  • IAS 38-compliant data asset valuation for balance sheet recognition
  • A new inorganic revenue stream from data you already own, zero capex
  • Data room-ready credential for M&A and financing processes
  • Governance gap converted to a capital investment with calculable ROI
Chief Executive Officer
A new revenue line from assets you already own.

Your board wants new revenue streams without new capital deployment. Your data is already generating value for your own operations. With DataVault, it can generate value for other industries too: insurers, AI developers, research institutions, and public sector bodies.

  • Inorganic revenue from latent, untapped data assets, no new capex
  • Cross-industry monetisation, GDPR-compliant by architecture
  • First-mover advantage before competitors discover their own data value
  • Competitive differentiation: data becomes a monetisable strategic asset
Chief Technology Officer
Compliant, architected, and fully auditable.

Your concern is data security, regulatory exposure, and governance liability. DataVault is built to address all three, not with contractual promises, but with system architecture that makes data leakage structurally impossible and every decision fully traceable.

  • On-Premise Agent: raw data never leaves Zone 1 of your infrastructure
  • OPA Rego policy engine: every scoring rule is auditable and replayable
  • REST and streaming API distribution with granular entitlement controls
  • SHA-256 signed credential with 7-year immutable audit trail
The DataVault report

Seven elements. One signed credential.

The report buyers rely on in lieu of their own due diligence, eliminating the 4–8 week parallel due diligence phase that stalls most data transactions.

Report Element 01
Scores and quadrant position
The Data Equity Score (DES, 0–90100) measures intrinsic commercial quality across five dimensions. The Market Readiness Score (MRS, 0–100) measures operational and compliance deployment readiness. Together they determine your commercialisation strategy and timeline to first revenue.
Illustrative output: Regional bank SME dataset
Data Equity Score (DES)62 / 100
Market Readiness Score (MRS)48 / 100
Quadrant positionHigh DES / Low MRS
Recommended strategyGovernance investment
Timeline to first revenue90–120 days
How we compare

The only platform that values and monetises your data.

Every existing tool serves a different master. Marketplaces transact. Valuation software prices companies. Consultants advise. None work at the dataset level with a monetisation route. That quadrant is ours.

CapabilityData EquityDawex73 StringsDeloitteGartner
AI-led dataset valuationYesNoNoNoNo
Self-service deliveryYesYesYesNoNo
Multi-lens valuation frameworkYesNoNoYesYes
Monetisation strategy outputYesNoNoYesNo
Accessible without consulting retainerYesYesYesNoNo
GCC and emerging market focusYesNoNoNoNo
Auditable, certifiable outputPlannedNoNoYesYes

"Trillions of dollars of data sits on balance sheets with no agreed value. Data Equity is the methodology that closes that gap."

Worked example

A regional bank's SME dataset: from €0 to €15.6M NPV.

8 years of credit behaviour. 35,000 entity records. Previously unmonetised. Legal team said GDPR blocked commercialisation. They were right about the raw data, and wrong about the derivative.

Asset profile
DatasetSME credit behaviour
Volume3.36M data points
Temporal depth8 years (96 months)
Governance levelL2 (self-assessed)
Prior monetisationNone
GDPR status (raw)Blocked
GDPR status (pseudonymised)Clear
62/100
Data Equity Score
48/100
Market Readiness
€0
Raw realisable
€9M
Derivative realisable
5-year revenue projection, Track B (pseudonymised derivative)
Revenue streamYr 1Yr 2Yr 3Yr 5
AI training rights (P6)€8.0M–––
DaaS subscriptions, 3 fintechs (P2)€0.5M€2.4M€2.8M€3.6M
Aggregated index, insurers (P3)€0.2M€0.5M€0.7M€0.9M
Total annual revenue€8.7M€2.9M€3.5M€4.5M
5-year NPV at 18% discount rate
€15.6M
vs €6.8M from a single one-time transaction
Pseudonymisation cost
€75k
12 weeks to first revenue
All figures illustrative. Actual outputs vary by dataset characteristics, governance level, and market conditions. Year 1 revenue is front-loaded by the AI training rights transaction. Most datasets will show a different profile with subscription revenue building from Year 2 onwards.
Use Cases

Your Buyers Have a Problem to Solve

We don't list datasets. We match outcomes to assets. See how leading organisations monetise data by solving real business problems.

🏦Lending

Credit Underwriting

Problem: Lenders need to approve more applicants without increasing default rates.

Data Type: Transaction, behavioural & alternative data

Outcome:

18% reduction in credit default prediction error

Explore case study →
🛡️Claims

Fraud Prevention

Problem: Insurers and fintechs lose millions annually to first-party fraud.

Data Type: Telemetry, identity & behavioural signals

Outcome:

31% improvement in fraud detection accuracy (modelled)

Explore case study →
📦Supply Chain

Demand Forecasting

Problem: Retailers carry 15–25% excess inventory due to poor demand signals.

Data Type: POS, supplier sell-through & location data

Outcome:

23% improvement in demand forecast accuracy

Explore case study →
🧠Compliance

AI Model Training

Problem: AI labs need high-quality labelled data at scale, without privacy risk.

Data Type: Annotated, synthetic & sector-specific datasets

Outcome:

AI training rights monetised across 7 licensing pathways

Explore case study →

Ready to unlock your data's value in your industry?

Book a Free Scoping Call
Monetization Pathways

Seven Ways to Monetize. All Protected.

Stay in control with standardized contracts, continuous compliance checks, and quarterly re-valuations. Buyers can\'t replicate this going direct - the platform is your moat.

📜

Annual Licence

Recurring
🤖

AI Training Rights

High Value
📊

Analytics Access

Popular
🔌

API Access

Scalable
📦

Bulk Export

Enterprise
🔍

Federated Query

Secure
💎

Exclusivity

Premium

Standardized Connectivity

Buyers connect once to the platform, then access any dataset. No custom integrations, no vendor lock-in risks. Just seamless, compliant transactions.

1
Secure API
2
Bulk Transfer
3
Federated Query
4
Streaming
5
Data Room
Getting Started

Your First 30 Days

Free scoping call. No preparation needed. No commitment.

📞
Day 1–3

Scoping Call

30-minute call with your Client Success Manager. Nothing to prepare.

📥
Day 3–8

Asset Intake

Candidate datasets shortlisted. Discovery Agent deployed.

📊
13–15

Computation

AI-driven five-lens valuation computation, and DataVault report delivery.

✅
Day 16–20

Review & Listing

CSM walkthrough. Marketplace listing approved.

🤝
Day 20–30

Buyer Matching

First buyer introductions arrive.

What You'll Need

RequirementDetailWho
Commercial authorityLegal right to commercialize candidate datasetsYou
Dataset descriptionsPlain-language descriptions of each assetYou
Read-only accessRead-only credentials for the Discovery AgentYour IT
Network egressHTTPS outbound connection (TCP 443)Your IT
MSLA signatureStandard form, typically reviewed in 2–4 hoursLegal

30 minutes · Free · No commitment

FAQ

Common Questions

9questions answered

No. The Discovery Agent runs in your environment. We receive only statistical summaries and structural labels. No data values, no records, no PII.

Regulatory constraints are modelled as part of the assessment. A transformed derivative often has higher realisable value than the raw dataset.

No. Receiving the DataVault report carries no obligation. Some organisations use assessments for internal purposes only.

The report captures conditions at time of assessment. Reassessment is recommended if the dataset changes materially or 12+ months have passed.

The DES is computed by a deterministic formula, not an AI model. Any party with the sub-score inputs can independently reproduce the score.

Only within boundaries you set. You configure buyer categories, minimum DES requirements, permitted delivery modes, and geographic restrictions.

The report provides a third-party, evidence-based valuation that acquirers can rely on in lieu of their own data due diligence.

Exclusivity is modelled as part of the Option Value lens. You retain complete control. The report quantifies the exclusivity premium.

We operate across ten verticals. Assets that are entirely unstructured with no extractable profile, or where rights are not held, are outside scope.

Start today

Your data is already valuable.
Let's prove it.

A 30-minute scoping call with a Data Equity Client Success Manager. We identify your highest-value dataset and give you a preliminary view of its commercial potential, at no cost and no obligation.