Which is better for finding off-market deals, Cherre or Reonomy?

Reonomy, for most acquisitions teams. Its core product is ownership data, contacts, transaction and debt history, and likely-to-sell signals — exactly the inputs an off-market sourcing workflow needs. Cherre doesn't generate off-market leads on its own; it makes whatever sources you feed it (including Reonomy) cleaner and joinable. If off-market sourcing is the goal and you're a lean team, start with a source like Reonomy; layer Cherre in later if data sprawl across multiple sources becomes the bottleneck.

Can you use Cherre and Reonomy together?

Yes, and many sophisticated firms do. The common pattern is Reonomy as one feed among several (alongside public records, ATTOM, internal Yardi/MRI data, and comps) with Cherre as the unification layer that resolves all of them into a single trustworthy entity graph. Reonomy answers 'who owns this and how do I reach them'; Cherre answers 'how does that connect to everything else my firm knows.' Running both gives you the source data plus the governance to use it consistently across teams.

Can I redistribute Reonomy data to clients or in deliverables?

No. Reonomy is customer-licensed with no redistribution — the data is licensed for your firm's authorized internal use. You can't resell it, pipe it into a client-facing deliverable, or pass it outside your licensed environment, and any automation that touches Reonomy data must respect those terms. The same principle applies to a Cherre deployment: Cherre governs and connects the sources you've licensed, but it doesn't grant rights to data you didn't license. The rule is simple — your license, your authorized use.

Does Cherre or Reonomy have an API for automation?

Cherre is built as an integration platform — connectors, resolved entities, and a queryable graph are the product, so programmatic access is core to how it's used. Reonomy offers a partner-gated API, with access and permitted use governed by your license. Both are real, usable integration surfaces, but they serve different goals: Cherre exposes a unified data layer to query, while Reonomy exposes its property/ownership dataset for sanctioned internal use. Note the contrast with CoStar, which has no sanctioned API and prohibits programmatic access entirely.

What are the best alternatives to Cherre and Reonomy?

As a Reonomy alternative or supplement, ATTOM is the closest — nationwide parcel, ownership, tax, and transaction data with documented, integrator-friendly APIs. Regrid is the parcel-boundary and land-data layer, strong for mapping and GIS-driven sourcing. CoStar is the broadest CRE dataset but works-alongside only (no API, exports under your own license). As a Cherre alternative, firms either build their own data warehouse or use other data-platform tools — we cover the full landscape in our best CRE data platforms guide. The right alternative depends on whether you're replacing the source (Reonomy) or the unification layer (Cherre).

How does AI automation fit with Cherre and Reonomy?

A data layer is raw material, not deal flow — turning a clean property graph or an owner list into screened, prioritized, contacted opportunities is manual work at most firms. AI automation closes that gap: property-enrichment automation reads from a Cherre graph, enriches records against your buy box, and syncs your CRM and underwriting tools; an AI deal-sourcing agent monitors Reonomy's owner and signal data, scores opportunities, and surfaces a prioritized list. The automation sits on top of whichever data layer you chose — it doesn't replace it — and it always operates within your license terms so nothing gets redistributed.

Should a 10-person CRE firm buy Cherre or Reonomy?

For most 10-person firms, Reonomy (or a comparable source like ATTOM) is the better first buy — it delivers fast time-to-value for an acquisitions team without needing a dedicated data function. Cherre is enterprise data infrastructure; its ROI shows up when you license many sources that don't reconcile and reconciliation work is a real cost across multiple teams. A lean firm usually starts with one strong source, then adds a unification layer only when data sprawl becomes the bottleneck. Either way, the fastest payback is automating the path from that data to a contacted deal.

Cherre vs Reonomy: Data Unification vs Property & Ownership Data (2026)

Q: Is Cherre a competitor to Reonomy?

Not really — they sit on different layers of the CRE data stack. Reonomy is a data source: property, ownership, contact, and transaction/debt data used to find owners and off-market opportunities. Cherre is a data-unification and warehousing platform that ingests, resolves, and connects the sources you already license into one property graph. In many deployments Cherre actually ingests Reonomy as one of several feeds, which makes them complementary rather than competitive. The real question isn't 'which one,' it's 'is my problem finding data (Reonomy) or governing it (Cherre)?'

"Cherre vs Reonomy" is one of the most common head-to-heads we get asked to settle — and it's the wrong fight. The two tools sit on different layers of the CRE data stack. Reonomy is a property and ownership dataset: who owns a parcel, how to reach them, their debt and transaction history, and signals that a building might trade. Cherre is a data-unification and warehousing platform: it ingests, resolves, and connects the sources you already license — including, in many deployments, Reonomy itself — so your firm has one clean property graph instead of a dozen disconnected exports.

If you're a data/analytics or acquisitions team choosing between them, the honest answer is usually "it depends on whether your problem is finding the data or governing it." This guide compares them on the dimensions that actually matter — coverage, integration posture, licensing, and lifecycle fit — names a real winner per use case, and then shows where AI automation changes the answer for both. NextAutomation is the automation layer that operationalizes either dataset into deal flow; we are not the dataset, and we'll say so plainly throughout.

Cherre vs Reonomy at a Glance

Dimension	Cherre	Reonomy
Primary job	Unify, resolve, and warehouse CRE data from many sources into one property graph	Provide property, ownership, contact, and transaction/debt data for sourcing and outreach
Layer in the stack	Infrastructure / data integration platform	Data provider / source feed
Buyer	Data, analytics, and IT teams at larger firms standardizing on a data layer	Acquisitions, sourcing, and capital-markets teams hunting owners and off-market deals
Coverage strength	As broad as the sources you connect — public records, third-party data, internal systems	Nationwide parcel, ownership, and contact data with off-market intent signals
Integration posture	Built as an integration platform — connectors, resolved entities, and a queryable graph are the product	Partner-gated API; access and use governed by your license
Licensing / redistribution	You bring your own licensed sources; Cherre governs and connects them	Customer-licensed, no redistribution — data is for your authorized internal use
Relationship to each other	Can ingest Reonomy as one of many sources	Can be a feed into a Cherre deployment

The single most useful framing: Reonomy is a source; Cherre is a system of record for sources. Many sophisticated firms run both — Reonomy as one of several feeds, Cherre as the layer that resolves them into a single trustworthy entity graph. They are far more complementary than competitive.

How to Decide: Buyer Criteria

Before you compare features, get clear on which problem you're actually solving. Score yourself against these criteria:

1. Is your problem finding data or governing it? If your sourcing team can't find owners and off-market opportunities, you need a source like Reonomy. If your analysts can find data but can't trust or join it across systems, you need a unification layer like Cherre.
2. How many data sources do you already license? One or two? A source feed is enough. Five-plus (CoStar exports, county records, Reonomy, internal Yardi/MRI data, comps) that never reconcile? That's the warehouse/entity-resolution problem Cherre exists for.
3. Who is the buyer internally? Acquisitions and capital markets pull toward Reonomy (owners, contacts, signals). Data, analytics, and IT pull toward Cherre (governance, lineage, one schema).
4. What's the output? Outbound owner outreach and an off-market pipeline argue for Reonomy. A BI dashboard, a portfolio data model, or feeding internal underwriting tools argues for Cherre.
5. What's your scale and budget? Cherre is enterprise infrastructure — it pays back when data sprawl is a real cost. Reonomy is approachable for an acquisitions team that just needs to find and reach owners.

The Honest Head-to-Head: Winner Per Use Case

Neither tool "wins" outright, because they're not the same category. Here's the objective call by use case:

Use case	Winner	Why
Finding owners & contacts for outreach	Reonomy	Ownership, contact, and entity-resolution data is its core product.
Off-market intent signals	Reonomy	Debt maturities, transaction history, and likely-to-sell signals are native.
Unifying many licensed sources into one graph	Cherre	Entity resolution and connectors are the entire reason it exists.
Feeding internal BI / data warehouse	Cherre	Built to be the queryable, governed data layer beneath your tools.
Single acquisitions team, lean budget	Reonomy	Faster time-to-value; you don't need a data team to get going.
Multi-team firm rationalizing data sprawl	Cherre	The ROI is in killing reconciliation work across departments.
Running both	Both	Reonomy as a feed, Cherre as the resolution layer above it.

One honesty note that's easy to get wrong: Reonomy is customer-licensed with no redistribution. The data is licensed for your firm's authorized internal use — you can't pipe it into a client deliverable or resell it, and any automation that touches it must respect that. Cherre, similarly, doesn't grant you rights to data you didn't license; it governs the sources you bring. Both honor the same principle: your license, your authorized use.

Where the Adjacent Players Fit

A Cherre-vs-Reonomy decision rarely happens in isolation — these are the data sources you're likely weighing alongside them. We cover the full landscape in our pillar on the best CRE data platforms, but in brief:

ATTOM — nationwide parcel, ownership, tax, and transaction data with documented, integrator-friendly APIs. A common alternative or supplement to Reonomy as a structured property-data feed, and an easy source to land in a Cherre graph.
Regrid — the parcel-boundary and land-data layer. Strong for mapping and GIS-driven sourcing; pairs with ownership data rather than replacing it.
CoStar — the broadest CRE market dataset, but it has no sanctioned API and its terms prohibit programmatic access. It is strictly works-alongside: your team exports under your own license and automations ingest those exports — never scrape or wire it directly. It is not a drop-in feed for Cherre the way ATTOM is.

The takeaway: Reonomy competes most directly with ATTOM as an ownership/property feed, while Cherre competes with building your own warehouse. CoStar and Regrid are complements, not substitutes, for either.

Where AI Changes the Answer

Here's the part both Cherre and Reonomy leave to you: a data layer is not deal flow. A clean property graph or a list of owners is raw material — turning it into screened, prioritized, contacted opportunities is manual work at most firms. That's the gap automation closes, and it's where NextAutomation sits. We are explicitly not the dataset and not the #1 data platform — we're the layer that operationalizes whichever data layer you've chosen.

Operationalizing a unification layer: If you've standardized on Cherre, our property enrichment automation reads from your resolved graph, enriches records against your acquisition criteria, and keeps your CRM and underwriting tools in sync — so the warehouse actually drives action instead of sitting in a dashboard.
Turning ownership data into pipeline: If Reonomy is your source, our AI deal-sourcing agent monitors owner and signal data, scores opportunities against your buy box, and surfaces a prioritized list — all within the bounds of your license, since the data never leaves your authorized environment or gets redistributed.
Bridging both: When you run Reonomy as a feed into Cherre, automation is what closes the loop — pulling resolved entities, applying your screening logic, and pushing matched deals to the people who act on them.

The principle mirrors the rest of the stack: automation reads outputs from your data tools and produces inputs for your deal team. You don't rip and replace Cherre or Reonomy — you put an intelligence layer on top so the data you're already paying for converts into deals. For the full picture of how this fits the broader toolset, see the complete CRE software stack.

Lifecycle Fit: Where Each Earns Its Keep

Mapping both tools to the CRE deal lifecycle clarifies when each pays off:

Sourcing: Reonomy leads — owner discovery, contacts, and off-market signals are exactly this stage. Cherre contributes by making sure the sourcing data joins cleanly to everything else you know.
Underwriting: Cherre's edge — a resolved property graph feeds models with consistent, trustworthy inputs; Reonomy contributes ownership and transaction context.
IC & Diligence: Cherre — lineage and a single source of truth matter when the IC asks "where did this number come from?" Reonomy supplies the ownership and debt history that supports the narrative.
Capital Raise: Indirect for both — clean portfolio data (Cherre) supports credible deal and market context in LP materials.
Asset Management: Cherre — ongoing portfolio-level data unification keeps reporting consistent over time.
LP / IR Reporting: Cherre — a governed data layer makes portfolio roll-ups and investor reporting repeatable rather than a quarterly fire drill.

The pattern is clear: Reonomy is front-of-funnel (sourcing); Cherre is the spine that runs the length of the lifecycle. Automation is what carries the value from one stage to the next.

The Bottom Line

Choose Reonomy if your problem is finding — owners, contacts, off-market signals — and you want fast time-to-value for an acquisitions team. Choose Cherre if your problem is governing — too many sources, no single trustworthy property graph — and you have the scale to justify enterprise data infrastructure. Run both if you're a multi-team firm that wants Reonomy's signals resolved inside Cherre's spine. Whichever you pick, the data layer is the beginning, not the end: the firms that win are the ones who automate the path from clean data to contacted deal.

If you want help mapping which automations give your firm the fastest payback on the data you already license, our free roadmap call is the place to start. And for the wider landscape of data sources, see the best CRE data platforms.