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 — no metadata required.

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Raven

Raven — Street Targeting narrowing to an exact address in Las Vegas, top match confirmed

No metadata required — a single image is enough.

TIME
7 days
From photo to actionable lead
PRECISION
5,000 km
Street-targeted accuracy
COVERAGE
1 city
Global reach
A new name / Effective 2026.04
Formerly GeoSpy
Now
Raven
Same model. Same team. Same work. A new name — as the first intelligence system from Graylark.
§01The Raven platform

Every pixel carries a clue.

Raven is Graylark's visual intelligence platform. We train AI to understand the world — so it can read every detail in an image and tell you what it means.

What would take hours of manual review returns as high-confidence intelligence in seconds.

Raven · Live geoestimation
Graylark · Raven core
INPUT · LOW-CONTEXT IMAGE
An empty concrete driveway through a lawn lined with live oaks — low-context source image
0.81foliage species
0.74sky gradient
0.69distant signage
0.58curb · concrete
0.52light angle
0.48pavement texture
INFERRED LOCATION
COORDINATE
30.2672° N
-97.7431° W
REGION
Austin, TX
RADIUS
1.2 km
CONFIDENCE94%
NEIGHBORHOODS
  • South Lamar 94%
  • Zilker 87%
  • Bouldin Creek 81%
  • Barton Hills 76%
No metadata · no landmarks · no text
Every pixel carries a clue.
Fragments in. Intelligence out.
§  Capabilities  ·  Today

One platform. Three answers.

Raven reads a single image and returns intelligence an investigator can act on — three distinct ways today, with more always in deployment.

INPUT  ·  ONE FRAME
Single low-context photograph fed into Raven A B C
NO METADATA  ·  NO LANDMARKS  ·  NO TEXT
A
FOLIAGE · BIOME
Texas live oak0.81
Subtropical · 32°–33°N0.74
B
STREET SURFACE
Stamped concrete · residential0.62
Curb paint · US-spec0.58
C
VEHICLE · MAKE / MODEL
2024 Ford F4500.90
White · service body0.86
Where
Geoestimation
South Lamar, Austin  ·  94%
§ 02
Which
Street Targeting
1204 Westmoreland Blvd  ·  ±3 m
§ 03
What
CAR-ID
2024 Ford F450  ·  90% match
§ 04
New capabilities always in deployment
§02Find Region·Geoestimation 02

No landmarks. No metadata. Just a region.

Geoestimation reads environment, structure, and context from a single image — returning ranked, high-confidence regions in seconds.

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
Vision transformer decomposes the frame into vegetation, soil, architecture, sky — matched against a global reference library.
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
§03Find Street·Street Targeting 03

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
§04Identify Car·CarID v2.0 04

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
§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
§06Outcomes 06

Act swiftly. Close faster.

Anonymized outcomes from partner agencies. Names and investigative details withheld under MOU.

Field testimonial
“Raven helped us apprehend a dangerous fugitive in under 20 minutes from a single window photograph. This platform is unbelievable — a true game-changer for law enforcement operations.”
Deputy Chief · State Bureau of Investigation · US

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.