What is Verinode?

Verinode is the first independent data trust for the restoration industry. It turns the data already sitting in a restoration operator's inbox and tools into peer benchmarks and process insights, delivered through a Chief Data Officer called IQ that surfaces the few decisions worth an operator's time each week, ranked by dollar impact. Verinode is an independent, for-profit company; its data-use policy is reviewed by an Operator Advisory Council, and it never sells operator data to insurance carriers, which is what makes the benchmarks worth trusting.

IQ is the operator-facing product, the platform an individual restoration operator signs into. The role it plays is closer to a Chief Data Officer than to software: it reads from the tools the operator already uses, structures what it reads, and surfaces the decisions worth acting on. It works the same way across every restoration segment: residential, commercial, large loss and CAT, reconstruction, and exterior and roofing.

No integration is required to start, and direct connection is there when the operator wants it. Email and calendar connect directly over OAuth (Google Workspace and Microsoft 365), and QuickBooks connects the same way for accounting. A documented public REST API moves the operator's own records in and out. Everything else (estimating, job management, field docs, CRM) flows in from exports and the inbox: upload, photo, paste, voice memo, call and meeting notes, and bulk import, with LLM extraction returning typed, normalized records. Records land in ten operational sections (Jobs, Vendors, Clients, Equipment, Fleet, Safety, Certifications, Compliance, Team, Recruiting) plus a Margin surface. Process mining runs continuously inside the operator's own data and surfaces drift, bottlenecks, and outliers as decision cards. Each card states the recommended action, the data behind it, the projected gain or risk, and the cost of inaction.

Once enough operators contribute, every number in IQ carries a peer comparison with an explicit validity label. Published benchmarks are labeled Indicative, Observed, or Verified according to how many operators stand behind them; nothing publishes below the cohort floor. A separate Early signal indicator appears on non-benchmark surfaces such as vendor peer ratings, where it discloses a count rather than a peer number. Identifying data sits behind a key scoped to the operator: no other operator or carrier can read it, no Verinode employee can browse or export it through any tool we operate, and our automated systems decrypt it only to run the product, with every access logged.

HQ is the network-intelligence product, built for franchise systems, operator associations, multi-location enterprises, and private-equity-backed platforms: anyone with a multi-operator network that needs visibility across it. HQ sits on top of IQ. Each operator in the network runs IQ for their own business, and HQ aggregates the network view above it.

Network leadership sees aggregates and compliance signals: network-performance benchmarks, certification posture, training rollout status, roll-up margin views, recruiting and retention trends, safety incident rates. Individual operator detail stays inside that operator's encrypted layer. HQ is not a job-management tool, an LMS, a CRM, or an accounting platform. It is the intelligence layer on top of the systems franchisees already use.

A data trust is an institution that aggregates information from a specific group of contributors and commits, structurally and publicly, to using it in their interest. Software you buy is the opposite arrangement: the vendor builds the product, you pay for access, and the data you generate inside it becomes the vendor's raw material for whatever they build next.

Three things differ. First, the institutional layer: a data trust has a published data-use policy, an advisory council that reviews how data gets used, and a published methodology open to audit. Second, the structural commitment: Verinode commits, in writing and in its architecture, never to sell operator data to insurance carriers. Third, the return: the same pooled intelligence that funds the company goes back to the operators who contributed it, as peer benchmarks, process-mined patterns, and drafted decisions.

Three protections, one for each part of the question. What stops it from being seen: identifying columns are encrypted with a Vault Key that belongs to the operator and is never stored on Verinode infrastructure in plaintext. No other operator or carrier can read those records, and no Verinode employee can browse or export them through any tool we operate. Verinode's automated systems decrypt them only to run the product, with every access logged.

What stops it from being sold: the data-use policy, codified in the Terms of Service, commits that operator data is never shared with anyone. When data flows to the cross-operator benchmark layer, the operator identifier is hashed before any observation is written, and a minimum peer-cohort size, higher for sensitive financial data, applies before anything is published.

What stops it from being stolen: row-level security is enforced at the database layer on every table, not just in application code. Even in a breach that reached the database, identifying records would stay unreadable without an authenticated operator session. Operators can request a full export of their data at any time.

Three sources, layered. The first is each operator's own data: process mining across their jobs, vendors, equipment, fleet, payroll, and certifications produces a baseline of what good and bad look like inside their own business, useful even before any peer comparison applies.

The second is the network. As more operators contribute, the benchmark layer fills in cohort medians and quartiles for margin, vendor pricing, cycle time, supplement approval rates, and more. A minimum peer-cohort size, higher for sensitive financial data, applies before anything is published, and every benchmark that clears it carries a validity label reflecting its cohort depth: Indicative, Observed, or Verified.

The third is independent research. Verinode Research publishes industry reports and methodology audits, each requiring multiple distinct sources. The methodology is published and open to operator audit, and sponsorship by software vendors, carriers, or TPAs is excluded by design. A canonical chart-of-accounts normalizer makes margin and cost data comparable across operators with different bookkeeping conventions.

Process mining instruments every operational section to detect drift, bottlenecks, and outliers as data accumulates: a vendor's pricing creeping above peer median, a certification 47 days from expiry, cycle time on water-damage jobs creeping up.

Every signal terminates in a decision card that states the recommended action, the projected gain or risk, the data behind it, and the cost of inaction. The operator can act on it, park it, or ask for the reasoning. Delivery is wherever the operator is working: email replies threaded into the inbox, mobile cards with native voice and camera, browser when they want to dig in.

A generic assistant with access to an operator's files can summarize estimates, draft emails, and surface patterns inside that operator's own data. The difference is the data above the model. Verinode operates on verified peer data contributed by members.

A generic assistant reasoning over your data alone can tell you your supplement approval rate. It cannot tell you whether seventy-three percent is good or terrible, because it has no access to other operators' rates to compare against. No model, however capable, can produce a peer benchmark from a single operator's data. To produce one, an institution has to pool data under a trust framework operators are willing to contribute to. Verinode is that institution for restoration.

The dominant restoration data aggregators collect operator data and sell access to whichever buyer pays. The bigger checks come from insurance carriers and real estate conglomerates, and a data business follows its largest customers. The result is a layer operators can subscribe to, but not one structurally accountable to them.

Verinode is the inverse: the same kind of data, structured around operator-side intelligence, with an Operator Advisory Council that advises on data-use policy and a published commitment that operator data is never shared with anyone.

No. Verinode reads from the stack an operator already uses rather than asking them to abandon it, which is the fastest path to a working benchmark layer. ERPs and job-management tools are systems of record for a single operator. Verinode is the intelligence layer across the network. The two are different products.

Staying out of those categories is also what keeps Verinode neutral. A trust that sold software competing with the tools it benchmarks would have a commercial interest in operators switching products, and that interest would show up in the benchmarks and recommendations. Neutrality on every operator's tool stack is what lets the comparison work.

The full Chief Data Officer interface across ten operational sections plus Margin. Vendor management, certification tracking, safety logs, compliance calendars, recruiting requisitions, and margin analysis all work without a peer cohort, and single-operator process mining works from the start. Research publications and Advisory benchmarks seed the network at launch, and peer benchmarks, including OSHA incident-rate benchmarks like TRIR and DART, deepen as operators contribute, with explicit confidence labels so operators always know what they are looking at.

Verinode is an independent, for-profit company, and no outside party controls it: not a carrier, not a vendor, not an operator faction. The Operator Advisory Council reviews the data-use policy and holds it to account; it is advisory only and does not govern the company's commercial decisions. The Council is restricted to active operator individuals; representatives of insurance carriers and TPAs are excluded by design. It is the structural answer to the question every operator should ask of any data layer aggregating across the industry: who reviews what gets aggregated, how it is published, and what stays private. Founding seats are reserved for operators contributing to the platform in its first year.