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Canonical

Canonical is a San Francisco-based early-stage venture firm investing $500K–$1.5M first checks in deeply technical, pre-product founders. It focuses on infrastructure for a post-AGI world, including physical AI and robotics, silicon, open and decentralized infrastructure, and programmable money rails.
San Francisco, USA

Fund Modeler


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Description

Fund Modeler is a Canonical-built, browser-based tool for modeling VC fund size, portfolio construction, reserves, fees, follow-on strategy, and exit outcomes. It calculates projected net and gross TVPI, DPI, IRR, carried interest, J-curve performance, and year-by-year cash flows; scenarios can be shared by link while remaining in the browser.

Category: FinOps Tooling

Power Law Outlier Lab


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Description

Power Law Outlier Lab is a Canonical Labs teaching tool for simulating venture-fund outcomes from inputs including fund size, investment count, reserves, ownership, follow-on strategy, loss rate, Pareto tail shape, fees, carry, fund life, and trial count. It reports net-TVPI distributions, return probabilities, quantiles, and return concentration metrics to illustrate the effects of portfolio construction and outlier outcomes; it explicitly says it should not be used to underwrite a manager.

Category: Venture Services

Data Centers & Neoclouds


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Description

Data Centers & Neoclouds is a Canonical Labs educational tool that explains the AI data-center buildout through seven stack layers and maps 31 companies. It includes illustrative analysis of infrastructure economics, GPU utilization, power availability, regulation, and long-term risks using public, point-in-time data.

Category: Data

Physical AI & Robotics


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Description

Physical AI & Robotics is a Canonical-built educational data tool covering physical-AI and robotics venture investment from Q1 2023 through Q1 2026. It presents investment and valuation comparisons, round-velocity analysis, geographic views, a 22-sub-sector explorer, methodology, and Canonical market perspectives.

Category: Data

Semiconductor Stack Disruptors


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Description

Semiconductor Stack Disruptors is a Canonical Labs educational research map of semiconductor picks-and-shovels, spanning raw materials, wafers, lithography, deposition and etch, inspection, foundries, and EDA software. It compares incumbent companies with challenger companies, provides Canonical’s investment-oriented viewpoints and watchlists, and documents its sources, methodology, caveats, and quarterly refresh approach.

Category: Data

Lookalike Finder


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Description

Lookalike Finder reconstructs a person’s public profile from the open web, extracts defining career traits, generates multiple neural-search queries, retrieves and de-duplicates candidates, and scores and ranks the closest career-DNA matches. It uses OpenRouter, Claude, and Exa to match people by career meaning rather than job-title keywords.

Category: Uncategorized

Dilution Lab


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Description

Dilution Lab is a browser-based educational capitalization-table tool. It lets users build scenarios from templates or scratch, add founders and an option pool, model SAFE and priced funding rounds, view ownership evolution across rounds, and compare exit proceeds under all-common and 1× non-participating preferred outcomes. It is explicitly not legal or financial advice.

Category: FinOps Tooling

Capital Call Planner


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Description

Capital Call Planner is a Canonical Labs tool for modeling private-market fund commitments. It lets users enter commitments and planning settings to forecast calls, distributions, liquidity-sleeve balances, portfolio J-curves, sustainable commitment pace, DPI, and TVPI, with editable Takahashi-Alexander pacing assumptions. It is presented as an educational model, not investment advice.

Category: FinOps Tooling

Decentralized AI


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Description

Decentralized AI is a Canonical Labs educational research tool that maps the decentralized AI ecosystem across training, inference, verification, agents, commerce, data, compute, and related layers. It presents project profiles, metrics, analysis, risks, and methodology for investors, founders, and technical teams; it is explicitly not investment advice.

Category: Uncategorized