Actively Raising

Foundational technologies, built from first principles.

We identify critical infrastructure problems where legacy approaches have become bottlenecks and solve them at the algorithmic level, engineered for modern silicon.

The Opportunity

Data is exploding.
Infrastructure hasn't kept up.

0+
TB/day from a single
satellite constellation
0+
petabytes in NASA's
Earth science archive
$0.0B
medical imaging
archival market

Legacy compression was designed for hardware that no longer exists. Organizations are forced to choose between fast processing and efficient compression. They need both.

The Suite: ten codecs, one substrate

RIPT and BVC, plus eight drop-ins.

Two flagship codecs, both patent-pending, both shipping as compiled binaries through the Developer Hub. Decoders are free; encoders are licensed.

Eight memory-safe drop-ins replace the C library a customer already runs, wire-compatible so they swap in with no migration. That compresses a pilot from multiple quarters to 2-6 weeks, and each one is a route into the flagship codecs.

See the suite overview.

RIPT
Coming Soon Patent Pending

A new codec

Adaptive predictive tiling. Wins on prediction-friendly data and on lossy modes. Targets new deployments where buyers control both encoder and decoder.

BVC
Coming Soon Patent Pending

A new codec, volumetric

Bitruvius Volumetric Codec, one codec for lidar point clouds and Gaussian splats. Lossless files smaller than the incumbents' lossy ones, decoded at GPU speed.

Plus the full Track B drop-in lineup

TurboLERC Esri LERC
TurboWebP libwebp 1.6.0
TurboJXL libjxl 0.11.2
TurboLZW libtiff LZW
TurboLZ4 liblz4 (C LZ4)
TurboZstd libzstd (RFC 8478)
TurboLEPCC Esri lepcc
TurboSPZ Niantic libspz v4
RIPT · Lossless ratio · Classification
0.0×
median across the corpus
peak 27× on flagship samples
RIPT · Lossy ratio at 1 m
median compression at 1m vertical error
peak 200×+ on flat high-res LiDAR DEM
TurboLERC · Encode speedup vs LERC
0.0×
median across all benchmarked domains
decode 1.4× median · same wire format

The products tell different stories. RIPT is a new codec with its own output; its compression varies by domain, with prediction-friendly data delivering 6×–20× lossless on high-res LiDAR and lossy modes pushing past 200× on flat high-res LiDAR DEM; basemap-resolution DEM and bathymetry compress orders of magnitude further (≈1,500–6,000× lossless). TurboLERC matches LERC's compression to 100% (same wire format, same bytes) and adds encode/decode throughput on top, peaking at 55× encode, peak 8× decode. All numbers from a refreshed benchmark corpus this quarter.

The Numbers

Backed by data.

RIPT lossless ratio per domain
0.0×5.0×10.0×15.0×20.0×Lidar Classification20.6×Multispectral6.4×Lidar Intensity2.3×Lidar Point Stats2.2×LiDAR DEM2.1×SAR Sub-Aperture1.9×

Solid bar = median across the matched corpus.Faded bar = 90th percentile (clipped to chart bounds when extreme outliers stretch beyond).

TurboLERC encode speedup vs LERC
0.0×1.0×2.0×3.0×4.0×LERC parityLidar Classification4.0×Multispectral3.6×Lidar Point Stats3.2×LiDAR DSM3.0×LiDAR nDSM3.0×LiDAR DEM2.9×

Solid bar = median across the matched corpus.Faded bar = 90th percentile (clipped to chart bounds when extreme outliers stretch beyond).

Market Opportunity

Any industry that stores
grids of numbers.

Satellite & Remote Sensing

30+ TB/day capture rates, petabyte-scale archives

Defense & Intelligence

Classified imagery, real-time ISR, tactical edge compute

Medical Imaging

$4.2B PACS market, CT/MRI/pathology archives

Geospatial & Mapping

Elevation models, LiDAR, Cloud Optimized GeoTIFF

AI/ML Infrastructure

Native int4/bf16 support, training data pipelines

Cloud & Scientific Computing

Storage egress reduction, HPC data movement

Technical Moat

Designed for how processors
actually work.

SIMD-First Architecture

Every predictor and transform operates on multiple pixels per instruction, exploiting the full width of modern processors. Not an optimization layer. The foundation.

Per-Tile Adaptive Selection

Instead of applying one strategy everywhere, RIPT independently picks the best predictor for each tile from an extensible library. Different data, different strategy. Automatically.

Cross-Platform Bit-Exact

Bit-exact identical output across NEON, AVX2, and the scalar fallback today. AVX-512 and SVE2 dispatch lands with benchmarks in Q1 2027. No prior scientific raster codec offers this guarantee.

Cache-Aligned Processing

Tiles are sized to fit in L1 cache. Zero-copy data paths. Every byte movement is intentional.

Defensibility

A three-layer moat.

Patents pending

Provisional patent filings cover the native Bitruvius formats: the RIPT adaptive tile-based system with its novel predictors, and the BVC volumetric codec for point clouds and Gaussian splats.

Compiled-only distribution

Both products ship exclusively as compiled binaries via the Bitruvius Developer Hub, including for paid licensees. The algorithm never enters source form on customer machines, materially raising the cost of reverse engineering.

Cross-platform SIMD substrate

A vendor-neutral dispatch layer covering NEON, AVX2, and scalar fallback today, with AVX-512 and SVE2 lined up for Q1 2027. Years of low-level engineering an open-source competitor would need to reproduce before they could even start matching feature parity.

Go-to-Market

Business Model

Free decoders, paid encoders

Decoders ship at no cost via the Developer Hub, encouraging adoption of the format and the wire-compatible drop-in. Production encoder licenses are paid: per-seat, per-transaction, OEM, and enterprise tiers.

Standards integration

Drop-in LERC replacement (via turbolerc), GDAL driver, Cloud Optimized GeoTIFF support, DICOM compatibility. Designed to slot into existing workflows without migration pain.

Interested in
learning more?

RIPT and TurboLERC are our first foundational technologies. We're raising our seed round to accelerate development, expand the corpus, and execute go-to-market.