OVERWRLD
Data Capacity Engine
via AI compression and data infrastructure

The world starts to expand.

Overwrld is a data capacity engine via AI compression and data infrastructure — a portable lossless compressor with cheap decode. We reached #1 on August 30, 2026 on the field's hardest public benchmark. Less data moved means less infrastructure required, and the saving compounds across storage, bandwidth, compute and energy.

We believe the most exciting worlds are the ones waiting to be discovered.

The Overwrld Nova — a four-pointed star through a tilted ring, in Earth, Sky, and Space
01/The problem

Data is exploding. Moving it is expensive.

Every AI workload, video stream, cloud application and data center pays the same tax, and it is charged four times over.

Storage × Bandwidth × Compute × Energy

Charged again
Storage
Paid to keep it
Charged again
Bandwidth
Paid to move it
Charged again
Compute
Paid to process it
Charged again
Energy
Paid to power all of it

Same bytes. Four invoices. The bill compounds.

Less data moved = Less infrastructure required

The industry's answer has been to build more: more racks, more fiber, more power. Compression is the only lever that makes what already exists carry more — the doorway through which the next world of capacity opens.

02/The proof

We reached #1 on August 30.

Two proofs, kept separate. The engine reached #1 on August 30, 2026 on Matt Mahoney's Large Text Compression Benchmark. The product is a portable binary that keeps most of the ratio and makes decode cheap enough to ship.

Large Text Compression Benchmark: altxs 1.0.0 reached #1 on August 30, 2026 by official total size
Public LTCB. We reached #1 on August 30, 2026 with altxs 1.0.0 on official total size.
enwik9 · 1,000,000,000 bytes in · lossless · decompressor counted
Overwrld altxs 1.0.0, #1 total106,924,811
Payload 93,434,410 + decompressor 13,490,401.
nncp v3.2, #2 total107,261,318
Next row on the same official total-size ranking.
Overwrld altxs 1.0.0, payload only93,434,410
Payload only. Official ranking is by total size.

Bars are zero-based and scaled to the largest total on this chart. Official ranking is by total size. Payload is shown for context.

Public rank
#1
Reached
Aug 30
Payload
93.4 MB
Total S
106.9 MB

We reached #1 on August 30, 2026 with altxs 1.0.0, by official total size — payload plus decompressor. That is the number a partner will check. The board is below.

SystemCorpusBytesSource
Overwrld altxs 1.0.0enwik9, payload + decompressor106,924,811ranked #1 August 30, 2026
nncp v3.2enwik9, total S107,261,318LTCB, as of August 30, 2026
Overwrld altxs 1.0.0enwik9, payload93,434,410same public row

Benchmark: Large Text Compression Benchmark (enwik9), lossless, decompressor counted. Program altxs 1.0.0. We reached #1 on August 30, 2026 by official total-size ranking. Payload 93,434,410 + decompressor 13,490,401 = 106,924,811 total. The 91.7 MB figure is a later model, not on the board, and is not the rank.

How each of these numbers is counted · Open the public board

03/Where we point it

Video first. Then the data center.

The engine is domain-general. The order we take markets in is not. We start where the bytes are densest and the decoder is ours to place.

04/How

Three ways to spend compute and buy bytes back.

Most compression products give you one setting. We choose the mode from what the asset is worth, because a cold archive read twice a year justifies compute that a live cache never will.

  • 01One model, many kinds of dataAmortized across domains
  • 02Specialised to a single assetClosest to that file's floor
  • 03Search, then verifyHighest value data only

How we get the bytes back

05/Why the lead holds

The lead compounds.

A standard is frozen the day it ships. AV1 is frozen. AV2 will be frozen. Ours isn't.

It improves after you buy it

Next year's version beats the one you signed for. No new standard, no hardware swap, no migration.

It specializes

Tuned to each customer's own data, not the compromise a global standard must pick for everyone at once.

The lead is defensible

A competitor cannot fork a moving target. Catching us means catching a system that keeps moving, not out-engineering one release.

06/The opportunity

The record is the proof. The product is the opportunity.

  • 01Technical moatA public, named result on the field's hardest open benchmark, and an architecture that keeps improving after release — in a field where every standard is frozen the day it ships.
  • 02Commercial productPortable compression binary designed to capture most of the breakthrough's benefit at a decode cost cheap enough to ship.
  • 03Massive customersStreaming and media, then cloud, then AI infrastructure, then enterprise data.
  • 04Business modelUsage-based infrastructure. Enterprise license plus usage.
07/The team

Built data and sales where the bytes already hurt.

The people shipping Overwrld have built data systems and enterprise sales across OpenAI, 84.51°, Databricks, and Amazon — the rooms where compression, capacity, and a closed deal are the same problem.

  • OpenAI
  • 84.51°
  • Databricks
  • Amazon
Conrad Lippert-Zajaczkowski
CEO

Conrad Lippert-Zajaczkowski

Founder. Listed author of altxs on the public Large Text Compression Benchmark.

D'Angelo Oberto-Besso Pando
COO

D'Angelo Oberto-Besso Pando

Operations. Keeps the company pointed at shipping, not slides.

Will Simpson
CPO

Will Simpson

Product. Turns a benchmark engine into something a buyer can place.

Brittany Dao
CRO

Brittany Dao

Enterprise sales. Fortune 500 closes including $33M CVS/Aetna at Adobe.

Engineer

Hoon

Core build. The binary has to land in a customer's stack, not a lab.

Engineer

Josh

AI/ML and data quality. The engine is only as honest as the data it is measured on.

Of Counsel

Samantha Vidal

Fractional counsel. Commercial and corporate work as the company takes on customers.

The team has closed or supported $180M+ in enterprise revenue. Brittany closed $98M in Fortune 500 deals, including $33M for CVS/Aetna at Adobe.

Get in touch

All that's left to do is step forward.

The fastest way to find out whether this pays off for you is to measure it on your own corpus, against your own tuned baseline.

hello@overwrld.ai

Waitlist