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Orca 1.4

Oceanir Team·Feb 24, 2026
XGitHub
Orca 1.4

Today we're releasing Orca 1.4 - a focused update that introduces better property-level insight to Oceanir. Where previous versions told you where something is, Orca 1.4 starts to tell you what's there and why it matters for decision-making.

Orca 1.4 is live with Miami only. We narrowed scope after lessons from Orca 1.0 through 1.3 and additional evaluation data. Those findings made it clear we needed a new architecture before expanding city coverage again.

Orca 1.3 gave us the infrastructure to scale. With that foundation in place, Orca 1.4 focuses on the insight layer - understanding not just coordinates, but the built environment around them. What kind of property is this? What's the surrounding area like? Is this a commercial corridor or a residential street?

These are the questions that matter for real-world property decisions - and they're the questions Orca 1.4 is designed to answer.

In internal evaluations, Orca 1.4 shows meaningful gains across all environment types - particularly in mixed-use areas and historic districts where property context is most valuable.

"Knowing where something is was always just the first step. The real value is understanding what's there and what you can do with that information."

- Internal product review, 2026

Better insight for smarter decisions

The core addition in Orca 1.4 is a property context layer. Every analysis now returns richer information about the built environment - building types, land use patterns, commercial density, and neighborhood character. This turns a location pin into usable property context.

Before - Location Only

Image → Analysis → Coordinates → Done

Now - Location + Property Insight

Image → Analysis → Coordinates + Property Type + Area Context + Property Signals → Decision-Ready Output

  • Property context - understands the built environment around a location, including building type, density, and land use patterns.
  • Selection precision - identify properties by characteristics that matter: commercial districts, residential zones, mixed-use corridors, industrial areas.
  • Neighborhood intelligence - every prediction includes richer context about the surrounding area, what kind of neighborhood it is, and how the area is developing.
  • Confidence scoring - better-calibrated confidence scores across all environment types. When the model says it's confident, it means it.

Internal evaluations

We evaluate Orca models on internal benchmark suites that test across different capabilities, built environment types, and ambiguity levels. The tables below show relative scores - not absolute accuracy numbers - and are intended to show directional improvements across capability groups.

The biggest gains are in property context and decision accuracy - the areas where Orca 1.4's new insight layer makes the most difference.

Capability Gains

Area
Orca 1.3
Orca 1.4
Visual Recognition
100
100
Property Context
35
82
Location Reasoning
55
84
Targeting Accuracy
40
79
Confidence Quality
45
81

Environment Performance (relative improvement over 1.3)

Environment
Improvement
Commercial Districts
78%
Residential Zones
62%
Mixed-Use Corridors
71%
Industrial Areas
55%
Historic Districts
83%
Suburban Sprawl
48%

Context Impact

Scenario
Basic
With Property Insight
Clear Context
88
94
Moderate Ambiguity
55
78
High Ambiguity
30
62

Why context changes everything

The practical difference between Orca 1.3 and Orca 1.4 is most visible in ambiguous scenarios. When a street photo could describe multiple types of properties, basic analysis can only give you coordinates. With property insight, you get the surrounding context that makes those coordinates useful.

The context layer is particularly effective in dense urban environments. Street-level features might not distinguish a residential block from a commercial one, but understanding the surrounding area - signage patterns, building materials, neighboring land use - almost always can.

Miami-first rollout

Orca 1.4 is live with Miami only. This is an intentional Miami-first rollout while we harden the new architecture and continue quality tuning before broader expansion.

We are expanding city-by-city again once benchmarks, calibration, and consistency meet our current quality bar.

Privacy architecture unchanged

The changes in Orca 1.4 are internal to how the model works. Our privacy guarantees remain the same: analysis data is retained only for limited periods under account policy, no user data is used for training, and all analysis records are encrypted per-user.

  • Per-user encryption - AES-256-GCM for all analysis records.
  • No training on user data - your images stay yours.
  • 30-day auto-cleanup - all analysis data is automatically removed.

Available now

Orca 1.4 is live in Miami only. Every Miami analysis now includes the new property insight layer - there's nothing to configure. Pro and Teams users get priority inference and access to the full property context breakdown.

Experience Orca 1.4

Orca 1.4 is currently available in Miami only. Upload an image and see the property insight for yourself.

Launch Oceanir→View Plans→

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