Frontline Visual Intelligence / Raven · RV-001 / 2026.04

From pixels to intelligence.

Raven is Graylark’s frontline visual intelligence platform. It reads pixels, identifies signals, and returns actionable leads in seconds, with no metadata required.

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Raven

Raven Street Targeting narrowing a low-context image to ranked street-level matches

No metadata required. A single image is enough.

§Meet Raven

Frontline visual intelligence, in action.

See how Raven turns low-context images and video into actionable investigative leads: from locating where footage was captured to identifying vehicles and assessing whether the content is real.

Dramatized scenario. Product interface and results shown are representative.
§01Find Region·Geoestimation 01

No landmarks. No metadata. Just a region.

Geoestimation analyzes the complete visual context of a single image and returns ranked location candidates. No EXIF or GPS metadata required.

One frame in. A city out.

Input
No metadata
Low-context phone photograph of a coffee cup on a balcony, out-of-focus trees in background
Single frame · no landmarks · no EXIF required
Raven · Geoestimation
Raven analyzes the complete visual context of the image — the natural environment, built surroundings, infrastructure, and the relationships between visible details.
Model view
Direct Inference
$ downsampled · luminance · edges
Returned in seconds
Live result
Raven Find Region result: Austin, Texas, United States · 90% match, 4 of 5 results in region
Identified
Austin, Texas · United States
Coordinates
30.3045°N, −97.7266°W
Radius
~15 mi
90%match · 4 of 5 in region
§02Find Street·Street Targeting 02

Built for low-context images.

Street Targeting delivers meter-level precision even when clear landmarks are absent, narrowing broad regions to exact locations in seconds.

Input
Phone photo
Phone photograph of a dark Lexus ES parked on a palm-lined residential street
Parked vehicle · residential street · no address in frame
Raven · Street Targeting
Refines a low-context image into a precise, real-world location using visual signal alignment.
Model view
Direct Inference
$ downsampled · street features
Top prediction confirmed
Top prediction · confirmed
Street Targeting result: 10 candidates ranked, top match confirmed at 8982 Lillyhammer Court
Identified
8982 Lillyhammer Court
Coordinates
36.1043°N, −115.2871°W
Rank
1 of 10
Topmatch · confirmed
§03Identify Car·CarID v2.0 03

Make. Model. Year. From a single image.

Analyzes partial visual signals across interior and exterior (body lines, materials, trim, controls, lighting) and compares them against a learned vehicle representation to identify make, model, and year with ranked candidates.

It returns ranked candidates scored by visual similarity, enabling fast and reliable identification.

Input
Partial · blurred
Low-resolution, blurred partial photograph of a pickup truck rear bumper corner
Rear bumper corner · blurred · no full-body view
Raven · CarID v2
Compares visual features to surface the closest vehicle matches: make, model, and year.
Model view
Vehicle ID Model
$ input → vehicle signature
Ranked by visual similarity
CarID workspace: source image with identification result (Chevrolet Silverado 2500, 2014, 77% match) beside 10 candidate matches ranked by visual similarity
Identified
2014 Chevrolet Silverado 2500
Candidates
10 ranked · make, model, year
Rank
Operator-selected · #8
77%match
§04Verify Image·AI & Deepfake Detection 04

Real, manipulated, or AI-generated?

Distinguishes genuine photos from AI-generated images, and catches deepfake or face-swap edits on real frames. When the image is synthetic, Raven names the most likely generator and ranks the rest by per-tool confidence.

Beta preview · accuracy is not guaranteed

Beta preview 1 image analyzed Verify · matches
Analyzed image: a person in tactical gear on a street, flagged as AI-generated
Uploaded image 110625-A-YG824-012.jpeg
Likely AI-generated
Signals consistent with a generative model. Closest match: Other.
Face manipulationFace-swap / deepfake signal
Deepfake (face swap) 2%
AI generatorsPer-tool confidence
Other 92%
Wan 2%
Qwen 1%
Imagen 1%
Kling 1%
DALL-E 1%
Grok 0%
Higgsfield 0%
Z-Image 0%
GAN 0%
FLUX 0%
Midjourney 0%
Adobe Firefly 0%
Beta preview · informational only · verify results independently
§05Case management 05

Case management, built for visual investigations.

Every search, pin, and source lives inside a shared case. Geolocations, vehicle IDs, and operator annotations pile onto one map.

Raven measures the distance between them, clusters the confident ones, and surfaces the leads that matter, automatically.

Auto-clustered. No manual correlation.

Sources · 6 added
Live case
GEO
Miami, FL: Find Region
14:22 · IMG_8125.jpg
94%
CAR
2019 Honda Civic Si
14:24 · bumper_partial.png
87%
OP
Home: S. Biscayne Dr
14:25 · operator pin
fixed
GEO
Little Havana block
14:31 · IMG_8141.jpg
89%
OP
Target address
14:35 · operator pin
fixed
TIP
Anonymous · street observation
1h ago · ingest channel
med
$ fragmented · mixed sensors · ungrouped
Raven · Case Intelligence
Measures distance between sources, scores proximity and confidence, and surfaces the tightest clusters as the case grows.
Leads · 3 surfaced
Auto-clustered
1
1423 SW 12th Ave · Little Havana
2 sources · 8 m apart · visual + vehicle
High
2
Biscayne corridor
3 sources · 142 m cluster · mixed
Medium
3
Target address · standalone
1 operator pin · unsupported
Low
$ ranked · distance × confidence × recency
One map. Every lead.
A burglary case: Sources panel with 4 geolocation results and 2 user pins, clustered numbered pins on a Miami-area map
IN PROGRESS · MIAMI
A burglary case
6sources
4geolocations
2user pins
2clusters surfaced

A safer world has no blind spots.

Raven is available to verified agencies and investigative teams. Book a demo to see it run on your own imagery.

Evaluating Raven for your agency? Read the Raven FAQ for answers on capabilities, accuracy, privacy, and procurement.