Companies · Crypto / Web3
NEW ORLEANS · Crypto / Web3 · refined from filed group “Other Technology” · founded 2025 · https://lucid.ai
Diligence memoA one-page analyst read on Lucid Holdings, LLC — recommendation, valuation, rhythm, risks.→Lucid Holdings, LLC has raised $64M over 3 rounds; too few niche peers to rank its valuation yet.
Synthesized from the figures below est. — every claim rests on a number shown on this page. Valuation uses the crypto/web3 sector profile.
Analyst read est. — computed against this company's niche peers in the same era. Inputs shown; not a quoted figure.
Procedural diagnosis est. — rule-based common-sense checks over the filing pattern, issuer name, activity cadence, and surfaced operating evidence.
Lucid Holdings, LLC behaves more like a recurring private-offering issuer than a conventional venture-backed operating company.
No named principal in this company's public records yet — see all operators below.
Explore how these operators interlock with other companies in the operator network.
Lucid Holdings, LLC is one of 196 Crypto / Web3 companies tracked from NEW ORLEANS, on record since 2025. By capital raised it ranks among the largest (ahead of 93% of sector peers), and among the largest by modeled valuation est..
Ranking is computed against this company's own sector cohort — reported capital is fact; valuation tiers are modeled.
AI analyst read est. — model-extracted from this company's public description, not a verified fact. 30%
operates a technology-led product inferred from public copy
Grounded in: “You are a venture analyst”
interactive video models
We are building universe simulations powered by interactive video models. We train video models that simulate hyper-realistic environments with immersive control, replacing hard-coded game or physics engines with dynamic neural networks. We built the fastest action-conditioned diffusion video model (running at 20+fps on a 4090 gaming gpu) to simulate minecraft. It is 5x faster than other minecraft World Models and was trained with 100x less resources. Our unique insight was relying on aggressive compression in our tokenizer (128x versus the traditional 8x), and because attention scales quadratically with # of tokens our model can run blindingly faster. Now we’re training a hyper realistic world model!
As reported in public records reported — not modeled.
Solid bars are reported offering amounts reported; hatched bars are the modeled post-money valuation est. — both on one shared scale so you can read raise-vs-worth at each round directly. Use the toggles to overlay data labels and the niche-peer / market average value lines.
The line shows cumulative reported funding over the period; + labels show new capital added between points when there is room. Toggle on-bar figures, plus the niche-peer and market averages, to read this company against its cohort. Benchmarks are modeled medians.
Stages are modeled from round size (public records carry no series label). No record for: Series A, Series B — the company may have raised it under a different exemption, merged it into an adjacent record, or skipped it. Sequence completeness: 60%.
Round size and date are reported; the stage label is inferred from round size (latest is Series C — a $40M–$100M round). Valuation is modeled from stage benchmarks scaled by the crypto/web3 sector profile. Directional, not a quoted figure.
Benchmarked against 196 companies in Crypto / Web3. Each bar is a median (the middle company, not an average — outliers don't skew it). Two yardsticks: real money raised (reported on Form D) and modeled value (our estimate est.). These are whole-sector medians across all stages, except the per-stage row.
Raised more than 93% of sector peers (real $). Modeled value above 96% of peers (estimate).
A tighter cohort than the sector chart above — only companies at the same stage (Series C) that last raised in the same ~3-year era, ranked by modeled value est. (not money raised). This is the exact set the analyst read compares against, so a like-for-like cohort is what makes "over/under-valued" meaningful.
Not enough valued peers in this cohort to chart positioning.
| Company | Stage | Raised · real | Value · est | vs peer med. |
|---|---|---|---|---|
| Gear Blockchain, Inc | Series C | $100.0M | $3.8B | 1.25× |
| Lucid Holdings, LLC this company | Series C | $64.2M | $2.3B | 0.75× |
Stage is inferred from round size est., not reported on the filing — a round's dollar size maps to a bucket: Pre-Seed <$1.0M · Seed $1.0M–$4.0M · Series A $4.0M–$15M · Series B $15M–$40M · Series C $40M–$100M · Series D+ $100M–$400M · Growth/Late >$400M.
| Stage | Amount · real | Announced | Post-money · est | Value · est | Conf. |
|---|---|---|---|---|---|
| Seed | $2.8M | 2011-11-07 | $14.0M | $115.2M | 85% |
| Seed | $1.4M | 2015-02-06 | $7.1M | $58.4M | 85% |
| Pre-Seed | $399K | 2015-02-06 | $2.2M | $20.4M | 85% |
| Series C | $60.0M | 2017-03-27 | $400.0M | $2.3B | 90% |
Step-up, pace versus the sector's normal cadence, and revenue/exemption moves — read straight from the reported round facts reported.
Predictive signals are modeled est. from this company's own cadence and step-up, plus sector benchmarks — directional, not advice. Peer set and a CSV export live in your analyst workspace.
Officers, directors and promoters named in this company's public recordsreported — the people who run it (not its investors). "Also runs" counts come from name-matching across all records, so verify before acting.
| Person | Role | Also runs | Tied since |
|---|---|---|---|
| Jon B. Kaiden | — | 1 other | 2017-03 |
| Patrick Comer | — | 1 other | 2011-11 |
| Andy B. Ellis | — | — | 2017-03 |
| Andy Walton Ellis | — | — | 2015-02 |
| Ben B. Hogg | — | — | 2017-03 |
| Brett B. Schnittlich | — | — | 2017-03 |
| Brett Walton Schnittlich | — | — | 2015-02 |
| Christina Walton Luquire | — | — | 2011-11 |
| Christopher Walton Schultz | — | — | 2011-11 |
| Donald B. Dodge | — | — | 2017-03 |
| Donald Walton Dodge | — | — | 2015-02 |
| James Walton Comer | — | — | 2011-11 |
| Jon Walton Kaiden | — | — | 2011-11 |
| Michael Walton McCrary | — | — | 2011-11 |
| Patrick B. Comer | — | — | 2015-02 |
| Paul B. Stouse | — | — | 2017-03 |
| Russ B. Pyle | — | — | 2017-03 |
| Walton B. Comer | — | — | 2017-03 |
Lucid Holdings, LLC is an official record sourced from the U.S. Securities and Exchange Commission (SEC). U.S. data is aggregated from SEC Form D filings.
Nearest neighbours across the whole database — matched on sector, stage and capital scale, and on shared operators (officers or directors named at both companies in public filings). A discovery shortlist, not a valuation cohort — verify before acting, the same way modeled figures are directional.
| Company | Sector | Stage | Raised · real | Value · est | Why similar |
|---|---|---|---|---|---|
| Dmg Blockchain Solutions Inc | Crypto / Web3 | Series C | $67.9M | $594.1M | same sector · same stage |
| One River Digital Asset Management ,LLC | Crypto / Web3 | Series C | $51.5M | $1.0B | same sector · same stage |
| Vortex Blockchain Technologies Inc. | Crypto / Web3 | Series C | $90.8M | $948.4M | same sector · same stage |
| Eastern Blockchain Technology Ltd. | Crypto / Web3 | Series C | $100.0M | $3.8B | same sector · same stage |
| Gear Blockchain, Inc | Crypto / Web3 | Series C | $100.0M | $3.8B | same sector · same stage |
| Life Code Global Blockchain Technology Cloud Service & Datacenters Providers LLC | Crypto / Web3 | Series C | $100.0M | $3.6B | same sector · same stage |
| Argo Blockchain Plc | Crypto / Web3 | Series B | $55.7M | $61.6M | same sector |
| Crypto Co | Crypto / Web3 | Series B | $53.4M | $1.1M | same sector |
Matched by meaning, not labels — a local language model reads each company's name, sector and description and ranks the closest in that learned space. This catches look-alikes that cross sector boundaries; the structured list above explains its matches, this one trusts the text. Directional, like every modeled signal here.
| Company | Sector | Stage | Value · est | Match |
|---|---|---|---|---|
| Keyframe Labs Turn agents into lifelike video calls with the word's best AI avatars | AI / ML | — | — | 76% |
| Vango AI Development platform that makes it 10x easier to improve visual models | Gaming | — | — | 75% |
| DigitalCarbon Transform Images And Videos Into Immersive 3D With AI | Robotics | — | — | 75% |
| Experiential Labs World models for AI agents | AI / ML | — | — | 75% |
| Crusoe Energy Holdings Inc. Crusoe provides next-gen AI infrastructure and cloud compute using an energy-first approach. Deploy AI workloads at scale with reliable performance and 24/7 support. | AI / ML | Growth/Late | $11.0B | 75% |
| One Robot World models for robot evals and training. | Robotics | — | — | 74% |
| SF Tensor Infrastructure for AI labs to focus on research. | AI / ML | — | — | 74% |
| Overshoot AI Infra for real-time vision applications | Public Safety & Security | — | — | 74% |
See where Lucid Holdings, LLC sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.
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