{"id":7229,"date":"2026-08-20T15:44:28","date_gmt":"2026-08-20T15:44:28","guid":{"rendered":"https:\/\/www.foote-tech.com\/en\/?p=7229"},"modified":"2026-08-26T09:18:08","modified_gmt":"2026-08-26T09:18:08","slug":"contracts-are-notcash-flowhow-trusted-operational-data-reframes-investment-due-diligence-for-green-projects","status":"publish","type":"post","link":"https:\/\/www.foote-tech.com\/en\/contracts-are-notcash-flowhow-trusted-operational-data-reframes-investment-due-diligence-for-green-projects\/","title":{"rendered":"CONTRACTS ARE NOT CASH FLOW"},"content":{"rendered":"\n

Executive perspective<\/mark><\/h1>\n\n\n\n
Core judgement <\/mark><\/strong> A long-term power-purchase, energy-service or performance contract defines when a customer should pay. It does not, by itself, prove that the project has delivered continuously or that future cash will reach the financing structure in full and on time. Investability depends on a reviewable evidence chain linking physical operation, contractual performance, settlement, invoicing, collection and debt service.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Green-project finance involves two related but distinct judgements. The first is whether an activity has a genuine and verifiable environmental purpose. The second is whether it can generate cash flow that is predictable, collectible and monitorable. The first governs green eligibility, environmental integrity and greenwashing risk; the second governs credit risk, valuation discounts and recovery of principal. Evidence for one cannot substitute for evidence for the other.<\/p>\n\n\n\n

Current green-loan and green-bond frameworks emphasise use of proceeds, project evaluation, management of proceeds, transparency and reporting.[1][2]<\/mark><\/sup><\/p>\n\n\n\n

For investors and lenders in energy and industrial-efficiency assets, however, an annual environmental report or one-off technical review still leaves a more immediate question unanswered: when equipment fails, readings go missing, customer operations change or contract pricing is adjusted, does the cash-flow case in the investment model still hold?<\/p>\n\n\n\n

This report examines distributed solar, behind-the-meter storage, energy performance contracting and industrial utilities. It asks how trusted operational data can support green lending, portfolio and warehouse finance, asset-backed securitisation (ABS), and real-world asset (RWA) or decentralised-finance applications. Trusted data infrastructure is not a replacement for legal, financial, credit or engineering judgement. It is an operational evidence layer that makes those judgements more traceable, comparable and continuously updateable.<\/p>\n\n\n\n

1. Why a long-term contract is not yet investable cash flow<\/mark><\/h1>\n\n\n\n

Energy and efficiency projects typically concentrate capital expenditure at the beginning and recover it over many years. The developer or energy-services company funds equipment, engineering and commissioning; the customer pays later for metered electricity, storage services, conforming utility supply or verified savings.<\/p>\n\n\n\n

The contract is the legal foundation of the cash flow, but it is not factual evidence that the cash flow has formed. A capital provider must still establish that the equipment exists and operates; readings correspond to the contractual boundary; delivery meets quality conditions; settlement uses the effective contract version; invoices and collections belong to the same asset; and cash is swept or distributed as the financing documents require.<\/p>\n\n\n\n

Risk transmission<\/mark> <\/strong> An equipment or data-source exception is not merely a technical event. It may alter billable delivery and therefore revenue recognition, debt-service coverage, borrowing-base eligibility, covenant tests and securitisation distributions. Conversely, reported revenue alone cannot prove that it arose from operating activity within the financed asset pool.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Table 1. A continuous evidence chain from physical assets to financial cash flow<\/strong><\/p>\n\n\n\n

Evidence layer<\/mark><\/strong><\/td>What the capital provider needs to establish<\/mark><\/strong><\/td><\/tr><\/thead>
1  Asset and boundary<\/td>A stable mapping among equipment, meters, project company, contracts and financed assets<\/td><\/tr>
2  Physical operation<\/td>The asset exists and operates, with actual output, efficiency and availability<\/td><\/tr>
3  Contract performance<\/td>Physical delivery meets contractual quantity, quality, timing and pricing conditions<\/td><\/tr>
4  Settlement and invoicing<\/td>Contract calculations reconcile to settlements, invoices and adjustments<\/td><\/tr>
5  Collection and debt service<\/td>Cash enters the designated account and supports costs, reserves and debt service<\/td><\/tr>
6  Continuing monitoring<\/td>The relationships remain reviewable after financing and exceptions trigger timely action<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

For a handful of projects, contracts, spreadsheets, emails and bespoke reporting may be enough to explain this chain. Once dozens or hundreds of assets enter a borrowing base or securitised pool, differences in definitions, time conventions, interfaces and manual adjustments compound quickly. Capital providers then bear not only project risk, but also uncertainty created by an inability to verify information repeatedly and at scale.<\/p>\n\n\n\n

2. Different green assets require different cash-flow evidence<\/mark><\/h1>\n\n\n\n

Green projects are not a homogeneous asset class. The same availability metric may indicate lost generation in a solar plant; for a battery it may also reflect a missed dispatch opportunity, degradation and revenue-allocation issues. In an energy performance contract, the central question may not be equipment output at all, but whether the baseline and adjustment factors are defensible.<\/p>\n\n\n\n

Table 2. Cash-flow logic, risk and data requirements by green-project type<\/strong><\/p>\n\n\n\n

Project type<\/mark><\/strong><\/td>How cash flow is created<\/mark><\/strong><\/td>Principal investment risks<\/mark><\/strong><\/td>Decision-useful operational data<\/mark><\/strong><\/td><\/tr><\/thead>
Commercial and industrial distributed solar<\/td>Metered supply or consumption x contractual tariff<\/td>Roof and asset title, offtaker credit, curtailment, downtime, degradation and meter mismatch<\/td>Revenue-meter readings, inverter data, self-consumption, availability, outages and degradation<\/td><\/tr>
Behind-the-meter storage<\/td>Tariff arbitrage, capacity services, demand response or shared savings<\/td>Tariff reform, dispatch strategy, battery degradation, safety and double counting of revenues<\/td>Charge\/discharge, cycles, SOC\/SOH, dispatch instructions, revenue attribution and alarms<\/td><\/tr>
Energy performance contracting<\/td>Verified energy savings x contractual sharing ratio<\/td>Baseline selection, operating-condition changes, counterfactual modelling, customer behaviour and savings disputes<\/td>Baseline versions, adjustment factors, production and operating data, measurement boundary and calculation trail<\/td><\/tr>
Steam, heat, cooling and compressed air<\/td>Conforming delivered volume x contractual price<\/td>Quality failures, continuity, fuel-cost pass-through and customer concentration<\/td>Flow, temperature, pressure, quality deviations, downtime, energy inputs and pricing parameters<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

2.1 Distributed solar: the revenue meter matters more than gross generation<\/mark><\/h2>\n\n\n\n

Revenue models commonly project generation, self-consumption, tariff and degradation. Yet inverter generation, revenue-meter export, customer consumption and settlement energy are not the same measure. Unless asset boundaries, meters and time intervals are mapped consistently, a statement that the plant is operating normally does not establish billable electricity. Roof rights, asset title, offtaker credit, curtailment, downtime and degradation remain central to cash-flow stability.<\/p>\n\n\n\n

2.2 Behind-the-meter storage: revenue stacking increases assurance risk<\/mark><\/h2>\n\n\n\n

A behind-the-meter battery may earn tariff-arbitrage savings, capacity revenues, demand-response payments or shared benefits. Investors need more than charge and discharge volumes. They must understand dispatch instructions, state of charge and health, cycle count, degradation, the tariff applied, and whether multiple revenue lines claim the same event. The evidence must therefore support safety, revenue attribution and useful-life assumptions at the same time.<\/p>\n\n\n\n

2.3 Industrial efficiency: savings are a constructed counterfactual<\/mark><\/h2>\n\n\n\n

Energy savings cannot be observed in the same way as electricity generation. They are generally calculated by comparing energy use before and after an intervention within a defined measurement boundary, with adjustments for changing conditions. This principle is central to the International Performance Measurement and Verification Protocol.[4]<\/mark><\/sup><\/p>\n\n\n\n

Baseline versions, production volumes, weather, operating hours and manual adjustments can all affect shared-savings revenue. Assurance does not mean pretending that the data are perfect. It means preserving original values, adjustments, reasons, methods and approvals so that an independent party can reproduce the result.<\/p>\n\n\n\n

2.4 Industrial utilities: volume is only part of delivery<\/mark><\/h2>\n\n\n\n

Steam, heat, cooling and compressed-air contracts usually pay for conforming delivery. Temperature, pressure, moisture and continuity may determine whether a period is billable at all, while fuel-cost pass-through can materially affect margins. A single flow reading cannot support the financing conclusion.<\/p>\n\n\n\n

3. Environmental integrity and credit quality must be tested separately<\/mark><\/h1>\n\n\n\n

Green eligibility asks whether proceeds fund qualifying activity and what environmental outcome the project creates. Credit analysis asks who pays, why they pay, whether collections cover debt service and what can be recovered after default. An asset may deliver substantial emissions reductions and still be unsuitable for a financing structure because of customer concentration, non-transferable contracts, defects in title or volatile collections.<\/p>\n\n\n\n

Trusted operational data can demonstrate how a project performs. It cannot independently prove legal title, contractual enforceability, invoice authenticity or an offtaker’s ultimate capacity to pay. Investors should treat data governance as one control within due diligence, not treat IoT, blockchain or third-party verification as credit enhancement in itself.<\/p>\n\n\n\n

The Hong Kong Monetary Authority’s climate-risk framework expects banks to identify, assess, monitor and manage climate-related risk, including enhanced due diligence for material counterparties where appropriate.[3]<\/mark><\/sup><\/p>\n\n\n\n

At project level, operational evidence therefore needs to work not only for a green label, but also for credit approval, post-closing review, covenant monitoring and portfolio risk management.<\/p>\n\n\n\n

4. The same data has a different job in each financing structure<\/mark><\/h1>\n\n\n\n

Table 3. Data responsibilities and due-diligence boundaries by financing structure<\/strong><\/p>\n\n\n\n

Financing structure<\/mark><\/strong><\/td>Capital provider’s core question<\/mark><\/strong><\/td>Role of trusted data<\/mark><\/strong><\/td>Matters requiring independent judgement<\/mark><\/strong><\/td><\/tr><\/thead>
Green or project loan<\/td>Is use of proceeds eligible? Can cash flow service debt? Is risk deteriorating after drawdown?<\/td>Tests output, availability, performance and environmental KPIs; informs DSCR assumptions and alerts<\/td>Borrower credit, security, title, enforceability, pricing and stress tests<\/td><\/tr>
Portfolio or warehouse financing<\/td>Which assets enter the pool? How do borrowing base and concentrations change?<\/td>Standardises asset identity, definitions, eligibility tests and continuing exception records<\/td>Asset isolation, account control, recourse, operator and offtaker concentration<\/td><\/tr>
Asset-backed securitisation<\/td>Can collections be aggregated reliably? Can tranches withstand loss and disruption?<\/td>Supports look-through analysis, servicer reporting, triggers and ongoing disclosure<\/td>True sale, bankruptcy remoteness, waterfall, credit enhancement and servicer replacement<\/td><\/tr>
RWA and DeFi applications<\/td>What legal right does the token represent? Does on-chain state remain aligned with the off-chain asset and cash flow?<\/td>Supplies verifiable off-chain inputs to oracles, smart contracts and investor reporting<\/td>Legal wrapper, custody, redemption, KYC\/AML, contract security, governance and liquidity<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

4.1 Green and project loans: from approval pack to continuing control<\/mark><\/h2>\n\n\n\n

For a single asset or small portfolio, lenders typically examine completion, revenue forecasts, offtaker credit, debt-service coverage, security and mitigants. Operational evidence can test output, availability, contractual performance and environmental KPIs, then translate failure, degradation or meter exceptions into post-closing alerts. Its value is not an automatic reduction in the interest rate. It is lower repetition in evidence gathering and earlier visibility of changing risk.<\/p>\n\n\n\n

4.2 Portfolio and warehouse finance: comparability comes before borrowing base<\/mark><\/h2>\n\n\n\n

A portfolio facility requires eligibility, exclusion, concentration and dynamic borrowing-base rules. If each asset defines generation, downtime, savings or conforming delivery differently, portfolio-level statistics conceal rather than reveal risk. Stable asset identifiers, a shared data dictionary, quality rules and an exception history are prerequisites for a comparable pool.<\/p>\n\n\n\n

4.3 Securitisation: look-through data supports risk allocation and surveillance<\/mark><\/h2>\n\n\n\n

Securitisation investors assess not only aggregate collections but also underlying exposures, payment priority, triggers, credit enhancement, liquidity facilities and default definitions. European rules require institutional investors to assess underlying exposures and transaction structure before investing and to monitor them during the holding period; disclosure standards further emphasise exposure-level and transaction-performance reporting.[5][6]<\/mark><\/sup><\/p>\n\n\n\n

For green-energy assets, continuous operating evidence can explain whether lower receipts arise from customer default, equipment downtime, degradation, meter failure or a pricing change. True sale, bankruptcy remoteness, the cash-flow waterfall and servicer replacement remain legal and structured-finance questions.<\/p>\n\n\n\n

4.4 RWA and DeFi: tokenisation does not manufacture trust in the underlying asset<\/mark><\/h2>\n\n\n\n

RWA is not a single financing product alongside a loan or ABS. It is a digital representation of a loan claim, revenue right, fund interest or other entitlement. The Bank for International Settlements notes that tokenisation requires a bridge between conventional assets and programmable platforms, while off-chain information must enter smart contracts through mechanisms such as oracles.[7]<\/mark><\/sup><\/p>\n\n\n\n

An immutable on-chain record proves only that changes to the on-chain state can be traced; it does not establish that the original information about equipment, title or cash flow was correct. The BIS has also highlighted how oracle, interoperability and governance weaknesses can compromise external-data integrity and system resilience.[8]<\/mark><\/sup><\/p>\n\n\n\n

An investor in an energy RWA must still review the token’s legal rights, isolation of underlying assets, custody, redemption, cash distribution, KYC and AML controls, smart-contract security and dispute resolution. DeFi is a mechanism or market rail; it does not remove these asset-level obligations.<\/p>\n\n\n\n

5. How trusted data changes an investment decision<\/mark><\/h1>\n\n\n\n

The financial value of data assurance is more specific than ‘greater transparency’. The transmission mechanism is: make operating facts more verifiable; reduce uncertainty in cash-flow estimates; improve scenarios, eligibility rules and covenant design; and thereby influence advance rates, valuation discounts, enhancement requirements, monitoring frequency and exception handling.<\/p>\n\n\n\n

5.1 Asset identity: prevent double financing and misattribution<\/mark><\/h2>\n\n\n\n

Equipment, meters, project companies, contracts and financed assets require stable relationships. Investors need to know whether an item has been sold, pledged, replaced or transferred, and whether the same revenue or environmental attribute is being used in more than one financing or asset issuance.<\/p>\n\n\n\n

5.2 Definitions: identical labels can conceal different economics<\/mark><\/h2>\n\n\n\n

A metric name is not a standard. The data dictionary should state the source device, measurement boundary, unit, sampling frequency, time zone, aggregation, missing-value treatment and contractual use. Cross-project comparison and portfolio statistics become meaningful only when definitions are consistent.<\/p>\n\n\n\n

5.3 Data quality: exceptions should be governed, not silently repaired<\/mark><\/h2>\n\n\n\n

Communications outages, sensor drift, manual entry and model changes are unavoidable. An investment-grade control preserves the raw value, corrected value, reason, approver and version. That record allows an independent reviewer to judge whether a correction is reasonable and whether bias is systematic.<\/p>\n\n\n\n

5.4 Operational-to-financial mapping: explain how delivery becomes cash<\/mark><\/h2>\n\n\n\n

The asset platform knows how much energy was delivered; the finance system knows what was invoiced and collected. The bridge is often a spreadsheet and an individual’s explanation. A capital provider needs to trace revenue and collection back to contract terms, settlement period, meter result and authorised adjustment to establish that the cash arose within the financed perimeter.<\/p>\n\n\n\n

5.5 Continuity and access: risk does not stop changing after closing<\/mark><\/h2>\n\n\n\n

A post-financing system needs permissioned access, data retention, privacy controls and auditable queries. Banks, independent engineers, verification bodies, trustees and investors may each see only the fields relevant to their role. Wider sharing increases the importance of access controls, commercial confidentiality and defined responsibility.<\/p>\n\n\n\n

6. Ten data questions every capital provider should ask<\/mark><\/h1>\n\n\n\n
    \n
  1. What is the financed perimeter, and can equipment, project company, contract, meter and collection account be mapped consistently?<\/li>\n\n\n\n
  2. Which metrics determine cash flow, and are their definitions, sources, units, time bases and measurement boundaries explicit?<\/li>\n\n\n\n
  3. How do operating readings map to contractual performance, settlement, invoices and actual collections?<\/li>\n\n\n\n
  4. Where are data missing, duplicated, anomalous or manually corrected; who approved corrections and can the calculation be reproduced?<\/li>\n\n\n\n
  5. When baselines, models, contracts or algorithms change, are earlier versions retained and is the economic effect assessed?<\/li>\n\n\n\n
  6. Do pooled assets use comparable standards, and can eligibility, exclusion and concentration tests be re-performed?<\/li>\n\n\n\n
  7. Which operating exceptions trigger a loan alert, covenant test, asset substitution or securitisation event report?<\/li>\n\n\n\n
  8. Can engineers, assurance providers, trustees or investors verify evidence independently within their authority?<\/li>\n\n\n\n
  9. If a data vendor, equipment manufacturer or operator exits, how are historical access and service continuity protected?<\/li>\n\n\n\n
  10. If the asset is tokenised, how are on-chain tokens, off-chain rights, cash distribution and equipment status kept aligned?<\/li>\n<\/ol>\n\n\n\n
    Investment implication<\/mark> <\/strong> If these questions can be answered only through a temporary data room, an individual’s memory or an issuer’s oral explanation, the investor is bearing more than project risk. It also bears operational-information risk: evidence may disappear, definitions may not be reusable and deterioration may be detected too late.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

    7. What trusted data infrastructure can – and cannot – do<\/mark><\/h1>\n\n\n\n

    It can improve<\/mark><\/h2>\n\n\n\n
      \n
    • the cost and speed of recurring evidence collection and reconciliation across systems and assets;<\/li>\n\n\n\n
    • traceability among assets, operations, contracts, settlement, invoices and collections;<\/li>\n\n\n\n
    • comparability, pool eligibility, exception surveillance and continuing disclosure;<\/li>\n\n\n\n
    • a shared evidence base for engineers, assurance providers, auditors, trustees and investors;<\/li>\n\n\n\n
    • reuse of underlying evidence for carbon accounting, carbon credits, energy-attribute certificates, sustainable-finance KPIs and RWA applications.<\/li>\n<\/ul>\n\n\n\n

      It cannot replace<\/mark><\/h2>\n\n\n\n
        \n
      • legal due diligence on title, permits, enforceability, true sale and bankruptcy remoteness;<\/li>\n\n\n\n
      • financial and tax diligence on accounting recognition, invoices, tax treatment and historical performance;<\/li>\n\n\n\n
      • credit judgement on ability to pay, security value, recovery and market-price exposure;<\/li>\n\n\n\n
      • specialist engineering judgement on design, useful life, safety, construction quality and future performance;<\/li>\n\n\n\n
      • carbon-asset qualification on methodology, additionality, entitlement and market acceptance;<\/li>\n\n\n\n
      • RWA governance on token classification, custody, redemption, contract security and regulatory compliance.<\/li>\n<\/ul>\n\n\n\n
        Boundary principle<\/mark> <\/strong> Trusted data does not turn a weak project into a strong asset and does not guarantee financing. It allows investment assumptions to be tested over time, brings deterioration forward and reduces the additional discount created when underlying facts are difficult to verify.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

        8. Financing due diligence as an entry point to the green-asset value chain<\/mark><\/h1>\n\n\n\n

        A business built only around carbon credits or renewable-energy certificates often has to educate project owners about monitoring, reporting and verification, methodology and environmental-rights value before a transaction exists. Demand is also exposed to eligibility, policy and market-price uncertainty. Financing due diligence responds to a more immediate capital constraint. Admission to a loan, fund, warehouse, securitisation or tokenised structure usually has a defined transaction date, accountable decision-maker and evidence requirement.<\/p>\n\n\n\n

        This makes financing a practical market-entry point for trusted data infrastructure. Capital providers define eligibility and surveillance standards; project owners upgrade their data capability in response. The same operational evidence can later support emissions accounting, carbon credits, renewable-energy certificates, sustainability reporting and RWA. Financing due diligence is not a departure from Climate Finance. It brings carbon-data expertise forward into the broader question of green-asset investability.<\/p>\n\n\n\n

        The commercial relationship is two-sided. Banks, funds, securities firms, asset managers and RWA platforms define and consume data standards. Developers, energy-services companies, special-purpose vehicles and aggregators normally fund remediation, integration and continuing service. Only when capital providers recognise a connection between data maturity and investment risk do issuers have a strong enough incentive to improve.<\/p>\n\n\n\n

        9. The role of Foote Technology and Carbonus<\/mark><\/h1>\n\n\n\n

        Foote Technology focuses on a layer that often sits between equipment systems, day-to-day operations and financial due diligence: converting real-world performance into permissioned, traceable and continuously updated investment evidence.<\/p>\n\n\n\n

        Carbonus is designed as an open and extensible reference architecture. It can connect to existing devices, control systems, SCADA and energy-management platforms, establish stable asset identity, shared definitions, quality records and processing history, and progressively link the following domains:<\/p>\n\n\n\n

        Evidence path<\/mark> <\/strong> Devices and sources  ->  project operation and performance  ->  contract performance and settlement  ->  invoices and collections  ->  financing surveillance and value extension<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

        Carbonus does not replace accountants, lawyers, rating agencies, independent engineers, verification bodies or financial institutions, and it does not equate ‘putting data on-chain’ with asset truth or credit enhancement. Its role is to provide a consistent operational evidence layer, with permissioning, third-party signatures and audit trails where appropriate.<\/p>\n\n\n\n

        For a capital provider, the first engagement may be an investment-grade data specification for one asset class or a surveillance pilot for a portfolio. For a project owner, it may be a financing-data readiness assessment that identifies gaps among asset identity, metering, contractual settlement and collection evidence.<\/p>\n\n\n\n

        Conclusion<\/mark><\/h1>\n\n\n\n
        Conclusion<\/mark> <\/strong> A functioning capital cycle for green projects requires more than long-term contracts and more than one-off due diligence. An asset becomes genuinely comparable, poolable and investable only when the way it operates, performs, earns and enters a financing structure can be verified continuously.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

        Trusted operational data cannot remove equipment, customer, contractual, legal or market risk. It can convert some uncertainty hidden in fragmented systems, inconsistent definitions and manual explanations into risk that can be identified, monitored and governed. For green lending, securitisation and RWA, that is both a transparency issue and a matter of pricing and capital protection.<\/p>\n\n\n\n

        Foote Technology seeks to work with banks, funds, asset managers, professional advisers and green-project operators to define finance-grade project-data standards and test them on a live asset or portfolio.<\/p>\n","protected":false},"excerpt":{"rendered":"

        Core judgement A long-term power-purchase, energy-service or performance contract defines when a customer should pay. It does not, by itself, prove that the project has delivered continuously or that future cash will reach the financing structure in full and on time. Investability depends on a reviewable evidence chain linking physical operation, contractual performance, settlement, invoicing, collection and debt service.<\/p>\n","protected":false},"author":1,"featured_media":7230,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[117],"tags":[125,122,121,120,124,123,118,41,119,127],"class_list":["post-7229","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-investment-risk-research","tag-asset-securitisation","tag-behind-the-meter-storage","tag-distributed-solar","tag-green-finance","tag-green-lending","tag-industrial-energy-efficiency","tag-investment-due-diligence","tag-mrv","tag-operational-data","tag-rwa"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/posts\/7229","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/comments?post=7229"}],"version-history":[{"count":15,"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/posts\/7229\/revisions"}],"predecessor-version":[{"id":7279,"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/posts\/7229\/revisions\/7279"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/media\/7230"}],"wp:attachment":[{"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/media?parent=7229"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/categories?post=7229"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.foote-tech.com\/en\/wp-json\/wp\/v2\/tags?post=7229"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}