Reaching the TransUnion credit data Dovly AI holds for each member

Every Dovly AI account is anchored to a TransUnion file the member has already consented to share. That is the important fact for an integrator: the valuable data here is not something Dovly invents, it is a structured copy of a regulated credit file plus the dispute and monitoring activity the app layers on top. The Play listing cites more than a million downloads, and Dovly's own marketing claims an average 82-point lift for long-enrolled premium members — its figure, its sample. What matters to a build is narrower and more concrete: a single-bureau report, a score with history, a dispute queue with states, and an alert stream, all sitting behind one authenticated session.

What a Dovly AI account actually stores

The surfaces below are what a logged-in member sees, named the way the app frames them. Free and premium accounts expose the same shapes at different refresh rates and dispute depth.

On the wire: the session and the TransUnion pull

The mobile client authenticates a member, holds a bearer token, and then reads the credit profile and the dispute and alert collections off the same authenticated origin. The sketch below is illustrative — exact paths and field names are confirmed during the build against a consenting account, not guessed here.

# 1. Member-consented session (mirrors the consent the user already grants Dovly)
POST /v3/auth/session
  { "email": "<member>", "secret": "<otp-or-pwd>", "device": "<id>" }
-> 200 { "access_token": "...", "expires_in": 3600, "plan": "free|premium" }

# 2. Credit profile — single bureau, refresh follows the bureau cadence
GET /v3/credit/profile           Authorization: Bearer <token>
-> 200 {
     "bureau": "TransUnion",
     "score": 671, "score_band": "fair",
     "pulled_at": "2026-05-12T...Z",
     "report": { "tradelines": [...], "inquiries": [...],
                 "public_records": [...], "utilization": 0.41 }
   }

# 3. Dispute ledger (depth depends on plan tier)
GET /v3/disputes?status=open
-> 200 [ { "item_id": "...", "bureau": "TransUnion",
           "round": 2, "status": "investigating",
           "reason": "not_mine", "opened_at": "..." } ]

# 4. Alert stream
GET /v3/alerts?since=2026-05-01
-> 200 [ { "type": "file_change|breach", "at": "...", "detail": {...} } ]

# Handled in the client: token refresh on 401, plan-tier branching,
# and back-off so a poll loop never expects data fresher than the last soft pull.
      

The shape we hand back

Raw app responses are normalized to a stable contract so your code does not break when the front end shifts. One illustrative slice:

{
  "subject_ref": "<opaque-member-key>",
  "bureau_coverage": ["TransUnion"],          // single-bureau, stated explicitly
  "score": { "value": 671, "model": "vantage_or_fico_as_pulled",
             "as_of": "2026-05-12", "series": [ { "d": "2026-04-10", "v": 654 } ] },
  "report": { "tradelines": [ { "creditor": "...", "balance": 0,
              "status": "current", "opened": "2019-03" } ],
              "inquiries": [], "derogatory": [] },
  "disputes": [ { "id": "...", "round": 2, "state": "investigating" } ],
  "plan_tier": "free",
  "freshness": { "source_pulled_at": "2026-05-12T...Z", "cadence": "monthly" }
}
      

What lands in your repo

The deliverable is built around the surfaces above, not a generic template:

• An OpenAPI 3 spec covering the session, credit profile, dispute ledger and alert endpoints as they behave for this app.
• A protocol and auth-flow report: the token lifecycle, refresh on expiry, plan-tier branching, and how the soft-inquiry cadence gates freshness.
• Runnable source — Python and Node.js — for login, score and report fetch, dispute and alert reads, with the normalization layer included.
• Automated tests against recorded fixtures for free and premium shapes, so a plan-tier difference fails loudly instead of silently.
• Interface documentation and a short data-retention and consent-logging note covering FCRA-governed credit data.

Routes in, and the one we'd actually pick

Three routes genuinely apply to Dovly AI.

User-consented session against the app's own surfaces

Authorized interface integration: a member authenticates, and the client reads the report, dispute and alert collections the way the app itself does. Reachable: everything a member can see. Effort: moderate, mostly the token lifecycle and plan-tier branching. Durability: good while the member's consent stands; sensitive to front-end change, which we cover with a contract test. We arrange the consenting test account with you during onboarding.

FCRA file disclosure, bureau-side

The consumer's own right to their TransUnion file disclosure is the most durable path to the underlying report. It is slower to wire and does not carry Dovly's dispute or AI layer, but it does not move when an app screen does. Good as the backstop the score and report fall back to.

Native artifacts as a fallback

Exported report PDFs and alert emails are a thin, brittle last resort — usable for a one-off reconciliation, not a live feed.

If this were our build, we would centre the consented session route, because it is the only one that carries the dispute ledger and the alert stream together, and keep FCRA file disclosure wired in as the part that stays stable when the app's front end is rebuilt.

Whose data this is, and the consent that moves it

This is FCRA-governed credit data about a US consumer, sourced from TransUnion. Two things follow. First, the member already grants Dovly permission to pull and hold that file on a soft inquiry through accredited partners; the integration mirrors that same consent rather than creating a new basis, so access stays the user's to give and revoke. Second, the consumer has an independent statutory right of file disclosure — to obtain what TransUnion holds about them — which is why the bureau-side route is a real backstop and not a workaround; the FTC summary of rights puts the cap on a paid file disclosure at roughly $16 in 2026. We operate the build as authorized, logged, data-minimized access, with consent records kept and an NDA where the engagement needs one. Score model labelling matters here too: the figure is TransUnion-only, and we mark it that way so nothing downstream treats it as a tri-bureau average.

What we plan for on a Dovly build

• Plan tier changes the data, not just the price: a free-tier token returns the single manual dispute selection and a monthly report, premium returns the unlimited AI dispute queue and a weekly one. We key the client and the schema to the member's tier so a free login does not look like an empty premium account.
• Freshness follows the bureau, not the app. The report only moves when a new soft pull lands, so we design the sync around Dovly's own cadence — monthly or weekly — and back the poll loop off accordingly instead of expecting on-demand refresh.
• It is a single-bureau source. We carry an explicit bureau_coverage field so downstream models never silently assume Equifax or Experian data is present.
• Mobile endpoints and the report view do change. We ship a small contract test that flags a shape change before it reaches your pipeline, and fold the check into ongoing maintenance.
• Access is arranged with you during onboarding — the build runs against a consenting member account or a sandboxed test profile. That is our step in the project, not something we ask you to settle before we start.

Screens from the app

Store screenshots, useful for confirming which surfaces a member actually reaches. Tap to enlarge.

The wider credit-app neighbourhood

Same-category apps an aggregator usually meets alongside Dovly AI. Listed for ecosystem context; a unified credit-data integration tends to span several of them.

• Credit Karma — free TransUnion and Equifax scores and reports for a very large US user base; two-bureau coverage where Dovly is one.
• Credit Sesame — credit monitoring with paid automated dispute filing; another single-bureau monitoring source to normalize against.
• Self — credit-builder installment account reporting on-time payments to all three bureaus; payment-history data rather than a report mirror.
• Kikoff — a low-cost tradeline that reports to the three bureaus; builder activity comparable to Dovly's tradeline feature.
• Borrowell — Canadian score monitoring and recommendations; relevant when an integration spans North American markets.
• Lexington Law — attorney-backed dispute service; dispute-workflow data parallel to Dovly's AI dispute ledger.
• Credit Repair Cloud — dispute-management platform used by repair businesses; client and dispute records at the firm level.
• Dispute Beast — automated dispute-letter generation; another dispute-centric dataset in the same lane.

What we checked, and when

This brief was put together from the app's own store listing and product pages plus the FCRA primary sources, reviewed May 2026. The integration model is based on how Dovly describes its TransUnion pull and dispute flow; exact endpoints are confirmed against a consenting account during the build, not asserted from the outside. Primary references: the Google Play listing, Dovly's how-it-works explainer, the FTC summary of rights under the FCRA, and the Federal Register file-disclosure rule.

OpenBanking Studio · integration desk notes, May 2026.

Questions a Dovly integrator actually asks

Is the score in Dovly AI a real TransUnion score or an estimate?

It is a TransUnion-sourced score and report, pulled through accredited partners on a soft inquiry and refreshed monthly on the free tier and weekly on premium, as Dovly describes it. The integration carries it through as a single-bureau figure, not a tri-bureau blend, and labels it that way so downstream code does not assume Equifax or Experian coverage.

Can you also pull the AI dispute history, or only the score and report?

Both. The dispute ledger — item, bureau, round, status — and the monitoring and data-breach alerts sit on the same authenticated account surface as the report. On a free-tier login the dispute record is the single manual selection rather than the unlimited AI dispute queue, so we key the schema to the member's plan tier.

Our users already link Dovly to their own credit file. Does that consent cover an integration?

That member consent is the basis we build on. The integration mirrors the access the user already grants Dovly, under their authorization, logged and data-minimized. We set the access up with you during onboarding rather than asking you to clear it first.

How current will the TransUnion data be once it is flowing?

As current as Dovly's own pull — monthly on the free plan, weekly on premium — because the data follows the bureau's soft-inquiry cadence rather than refreshing on demand. A working build is normally ready in one to two weeks.

The thing we hand over is a runnable client for the Dovly session plus the credit-profile, dispute and alert reads, with an OpenAPI spec, tests and interface docs around it. Source-code delivery starts at $300, invoiced only after we deliver it and you have confirmed it works; or skip the build entirely and call a hosted endpoint we run, paying per call with nothing upfront. Tell us the app name and what you need from its data at /contact.html — the consenting access and the compliance paperwork are arranged with you from there, and a typical build is ready inside one to two weeks.