You find a photo that seems to support a story. The caption names a city, the buildings look plausible, and an AI tool drops a pin nearby.
Then an editor asks a simple question: “How do we know?”
Suddenly the coordinate is only part of the job. You need to explain what the photo shows, why the candidate fits, and whether another place fits just as well.
GeoSeer and Oceanir both take that question seriously. Each offers more than a bare location prediction. GeoSeer emphasizes gathering and cross-checking evidence across media and research tools. Oceanir puts particular attention on visual evidence review, alternative candidates, and records that another person can inspect.
They overlap enough to deserve a proper comparison. Their differences become clearer once you follow the work beyond the first pin.
Published by GeoSeer using public product information checked on October 14, 2026. Pricing and access can change; benchmark results discussed here are vendor-reported.
GeoSeer vs Oceanir at a glance
| Question | GeoSeer | Oceanir |
|---|---|---|
| Main emphasis | Agentic investigation using visual, web, and geographic evidence | Visual location estimation and evidence review |
| Everyday inputs | Images, related image sets, supported video, media URLs, and text-only events | Photo analysis and multi-photo review queues |
| Deeper workflow | Agent Mode and Event Mode | D3 analysis; Manta through Enterprise |
| Review tools | Ranked candidates, reasoning, map and Street View comparison | Supporting/conflicting clues; Pro exports and rejected candidates |
| Free option | One Fast Mode web search daily; 10 total API calls | Basic D1 location checks without sign-in |
| Paid entry | $19/month, or $9/month billed annually | $10/month with 30 recurring credits |
| Developer access | Public media/event API with streaming support | Paid personal API; enterprise production and batch access |
Two ways to make a location answer useful
GeoSeer follows clues across the investigation
GeoSeer combines geographic estimation with research tools. Its agents can examine the scene, inspect available metadata, search for related material, and check candidate locations against maps and reference imagery.
The benefit is easiest to imagine with an ambiguous photo. Several cities might have the same building style. A fragment of text or a distinctive bridge can create a more specific lead, which then needs to agree with the geography.
GeoSeer can use that surrounding evidence as the search develops. Its Agent v1 overview describes the staged investigation, while its API documentation shows how coordinates and reasoning come back together.
For a researcher, the attraction is continuity. You can work from the image, bring in more context, and move toward a candidate you can inspect without treating each clue as a separate task.
Oceanir makes the visual case easier to review
Oceanir's geo-estimation reads scene-level clues without using metadata. It weighs features such as architecture, road infrastructure, signage, and vegetation, then returns candidates with evidence for review.
Its deeper workflow pays attention to disagreement. Supporting clues are useful, but a reason to reject a tempting location can be just as valuable. Pro includes rejected locations and evidence exports, which can help when a result must be handed to a colleague.
Oceanir has also expanded beyond broad estimation. Its Manta announcement describes Geo-Estimation, Ground for finer localization where reference coverage supports it, and Verify for visual matching review. Manta joins the everyday Orca offering and currently requires an Enterprise agreement.
That distinction matters: evaluating Oceanir's personal subscription is different from evaluating its full enterprise platform.
What the accuracy numbers actually tell you
Oceanir publishes distance-based results on OSV-5M: 45.77% of photos within 25 kilometers, 81.83% within 200 kilometers, and a median error of 30.5 kilometers. Its geo-estimation page gives those thresholds explicitly.
Those numbers describe broad visual estimation on that benchmark. They are useful for understanding the model, but they are not a street-address success rate for Ground or a measurement of your newsroom's photos.
GeoSeer's published evaluations use different image sets and workflows. The two companies' published figures do not form a matched test, so they cannot establish a direct accuracy ranking between the products.
For your own comparison, use a few known-location photos and ask three questions: How far away is the first candidate? Does the explanation contain clues you can check? How long does it take to reach a verified conclusion?
That last question is especially revealing. In research work, an answer earns its value when you can establish why it fits.
Pricing: a credit is not a complete search
Oceanir has the lower monthly subscription entry price. The allowances need a closer look, though.
| Plan | Price | Recurring allowance |
|---|---|---|
| GeoSeer Starter | $19/month, or $9/month billed annually | 100 web searches and 100 API calls/month; all analysis modes |
| GeoSeer Pro | $69/month, or $29/month billed annually | Unlimited web searches and 1,000 API calls/month |
| Oceanir Starter | $10/month | 30 credits/month, shared with API use |
| Oceanir Pro | $29/month | 100 credits/month, shared with API use; evidence exports |
| Oceanir Enterprise | Custom | Manta, team workflows, and agreed production access |
The key unit is Oceanir's D3 analysis, which uses 10 credits per run. If all your recurring credits go to D3, Starter covers three detailed analyses per month and Pro covers ten. Purchased packs cost roughly $0.60–$0.80 per credit, putting a D3 run funded from those packs at roughly $6–$8. These figures come from Oceanir's pricing page.
That can suit occasional deep reviews, particularly when the exports are useful. For frequent investigations, GeoSeer's included search and API allowances give you more room to work. Its current plans are listed in the GeoSeer pricing section.
The outputs are different, so the allowances are not a claim that each analysis does identical work. They are a practical way to estimate how quickly your monthly budget might run out.
Related images, queues, video, and events
“Multiple photos” can mean two different things.
You might have three views of the same junction and want them to inform one location search. Or you might have twenty unrelated photos that need separate review.
GeoSeer supports up to three related images as input. Oceanir's paid web queues help organize several photos, with each located independently. Its queue FAQ makes that distinction explicit. Both are useful, but they solve different workflow problems.
GeoSeer's scope also includes supported video input and Event Mode. If the next assignment is a developing incident with only a text description and a few reporting links, you can research its location without first finding a suitable photo. Our Event Mode introduction explains the intended use.
For journalists and OSINT analysts, that flexibility is a substantial advantage. The available evidence rarely arrives in the same format every time.
Evidence records and privacy deserve a place in the decision
Oceanir's Pro evidence exports are a clear strength when work needs a portable review record. A researcher can retain the clues, rejected candidates, and reasons alongside the proposed location.
Oceanir also documents privacy measures including per-user encryption, coordinate rounding, and automatic cleanup in its privacy architecture article. Those are worth examining if your organization has specific requirements for non-public source material.
GeoSeer's review workflow emphasizes ranked candidates, explanations, and visual comparison. That suits the active investigation: checking the source scene against a suggested place and sharing the result with someone who can help assess it.
The buying question is what your team needs to carry forward. A formal exported record may point toward Oceanir. A workflow that keeps gathering evidence across changing inputs makes GeoSeer particularly appealing.
Which tool would we start with?
Oceanir belongs on your shortlist if detailed photo review and exportable evidence are central to the job. Its free D1 check is an easy introduction, and its Enterprise offering deserves separate evaluation when Manta or shared cases matter.
For a wider research routine, we would start with GeoSeer. Images, video, text-described events, and a public API can sit within one workflow. That is useful when today's task is a street screenshot and tomorrow's is an incident with incomplete reporting.
You can also learn something by trying the same known-location photo in both. Compare the evidence as carefully as the pin. The better fit is the one that helps you finish the work with fewer unresolved questions.
Common questions about GeoSeer and Oceanir
Can both tools find a photo's location without metadata?
Yes. Both analyze visual geography. Oceanir says its geo-estimation does not use metadata; GeoSeer can inspect metadata when present and investigate visual clues when it is absent.
Does Oceanir's $10 plan include 30 detailed analyses?
It includes 30 recurring credits. D3 uses 10 credits, so that allowance covers three D3 analyses if spent entirely on that depth. Basic D1 checks remain free.
Which is better for mixed-media OSINT research?
GeoSeer is a practical fit when you regularly move between photos, video, and text-based incident research. Oceanir is particularly worth considering when structured photo review and evidence exports are your main requirements.
Try GeoSeer with a photo you want to understand, then check whether the evidence answers the question behind the location.