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.
satellite constellation
Earth science archive
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.
RIPT and BVC are the two native Bitruvius formats — RIPT for scientific raster and
elevation, BVC for volumetric (lidar point clouds and Gaussian splats). Both are
patent-pending, both ship as compiled binaries through the Bitruvius Developer Hub, and
both decode for free with licensed encoders. BVC's lossless files come in smaller than the
incumbents' lossy ones.
Track B is the drop-in lineup — eight memory-safe codecs that replace the C upstream a customer already runs, wire-compatible so they swap in with no
migration: TurboLERC (Esri LERC), TurboWebP (libwebp), TurboJXL (libjxl), TurboLZW (libtiff
LZW), TurboLZ4 (liblz4), TurboZstd (libzstd), TurboLEPCC (Esri lepcc), and TurboSPZ (Niantic
libspz, 3D Gaussian Splats). Track B compresses pilot duration from multi-quarter to 2-6
weeks and creates a 2-3x design-partner multiplier. See the suite overview.
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.
A new codec — volumetric
Bitruvius Volumetric Codec — one native format 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
SIMD LERC2, wire-identical; faster encode/decode, no migration.
Memory-safe (CVE-2023-4863) WebP drop-in.
Tiled-geospatial JPEG XL: bit-exact, smaller than the cjxl -e1 fast preset, memory-safe; ~42–71× faster per-core encode than the -e7 effort that matches its size.
1.15-1.20× faster; 10× via parallel batch API.
2.05× decode / 1.49× encode vs C lz4, ≈equal size.
Faster encode L5+, smaller output at L1/L9.
1.75-1.89× point-cloud encode/decode.
4-7× encode; decode beats the reference in every mode; 3D Splats.
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 — peak 55× encode, peak 8× decode. All numbers from a refreshed benchmark corpus this quarter.
The Numbers
Backed by data.
Solid bar = median across the matched corpus.Faded bar = 90th percentile (clipped to chart bounds when extreme outliers stretch beyond).
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 Q3 2026. 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 Q3 2026. 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.