Dark Matter · R&D — Institutional capability, without the headcount.

01 /The Problem

Institutional complexity. Lean teams. Spreadsheets holding it together.

Most investment firms — funds, RIAs, family offices, asset managers — run on manual processes. Data scattered across custodians, prime brokers, and spreadsheets. Research, reporting, and monitoring done by hand. A direct deal or new mandate lands and diligence swallows the team for months.

The work is automatable. But building the system properly means standing up an engineering team you can't justify hiring. So it doesn't get built, and your best people spend their weeks re‑keying data instead of making decisions.

57%

of investment firms cite lack of internal tech expertise as their #1 barrier

Most

middle‑ & back‑office workflows are still spreadsheet‑bound across the industry

~70%

of asset managers say tech debt and integration are blocking automation

Months

one new mandate or direct deal can dominate a lean team, end to end

Sources: Citi Private Bank Global Family Office Report 2025 · UBS Global Family Office Report 2024 · Deloitte / EY industry surveys, 2024.

02 /What We Build

One capability. Pointed at your hardest manual work.

01

Diligence systems

Read an entire data room, verify management's claims against the source documents, and surface what matters — with a citation to every page, so it stands up to your investment committee. Months of work, compressed into days.

02

Data consolidation & reporting

Pull holdings across every custodian, bank, and asset class into one verified view. Automated reporting that turns a multi‑day manual process into minutes — and gives you the clean data layer that AI actually needs.

03

Research & monitoring infrastructure

Live engines that aggregate market, portfolio, and on‑chain data into a single source of truth, with an analytical layer that answers questions instead of making you dig through tabs.

04

Custom builds

If it's financial, document‑heavy, and done by hand today, it can be built. Scoped to your exact workflow — not a generic platform you bend to fit.

Diligence & forensics

Full data‑room ingestion (PDFs, decks, 10‑Ks) → structured
Claims‑vs‑data cross‑check, cited to source page
Beneish M, Altman Z, Piotroski F forensic suite
Management‑memo verification & red‑flag triage
Committee‑ready memo output, one click

Reporting & data layer

Multi‑custodian holdings consolidation (cash to derivatives)
Statement / K‑1 / capital‑call PDF → structured data
Position & performance reporting, scheduled or on demand
Reconciliation against custodian and bank feeds
Clean, AI‑ready data layer the whole firm can query

Research & monitoring

Live market‑data pipelines (equities, crypto, macro, energy)
13F intelligence and ownership‑change alerts
18‑method intrinsic‑value ensemble
Conversational analytical layer over your data
Custom AI assistants trained on your portfolio & mandate

Execution & ops

Backtesting and signal infrastructure (tick‑level if needed)
Order management, execution analytics, slippage attribution
Risk dashboards: exposure, concentration, scenario
Internal workflow automation across front / middle / back
Investor‑relations reporting and audit‑grade trails

Every item above is something we already operate inside the Dark Matter Terminal. We don't research the problem — we adapt the solution.

03 /Proof

We built this to run our own fund.

We run a systematic, market‑neutral fund. To operate it, we built the Dark Matter Terminal — a live market‑intelligence system spanning forensic accounting, an 18‑method valuation ensemble, a live 13F reader, dark‑pool tagging, and AIS shipping‑flow tracking, fronted by a conversational analytical layer (with voice) that reads every engine and answers any market question with cited, evidence‑based research.

Built end to end, in‑house. This isn't a slide deck — it's production infrastructure the fund trades on every day. Most firms describe systems like this in a five‑year plan. We run ours daily, and it's the proof of what we'll build for you.

Dark Matter R&D Diligence Engine — a forensic diligence memo showing an ELEVATED RISK verdict with 4 of 5 management claims contradicted by the numbers, three forensic scorecards (Beneish M-Score, Altman Z-Score, Piotroski F-Score), and a claims-versus-data table

Our Diligence Engine, run on a sample data room: it read the target's management presentation, cross‑checked every claim against the financials, and flagged 4 of 5 claims contradicted by the numbers — margins called "expanding" that had contracted, "deleveraging" while debt doubled, "strong cash conversion" at 27%. The same forensic engine we run on our own fund, turned into a committee‑ready deliverable. Weeks of an analyst's work, in minutes.

Dark Matter Terminal — the intrinsic value engine: an 18-method valuation ensemble showing blended fair value versus market price with a five-year history

Dark Matter Terminal — the forensics engine: Beneish M-score, Altman Z-score and Piotroski F-score computed from reported financials

Real, unretouched views from the Dark Matter Terminal — the same class of consolidation, diligence, and analysis we'd build into your stack: the Oracle answering a live market question, the 18‑method intrinsic‑value engine, and the forensic‑accounting screen. Public‑market research only; no positions, returns, or performance shown.

04 /How It Works

Scoped, staged, and risk‑reversed.

01

$7,500

Scoping sprint

A fixed‑fee sprint to spec your exact workflow, data sources, and the build, with a working prototype on your real data. Fully credited toward the build if you proceed — and if the spec isn't right, you walk with the work and owe nothing further. You know precisely what you're getting before you commit.

02

Milestone‑gated

Milestone build

Delivered in stages tied to working deliverables on your data. You don't pay past any milestone unless it's delivering exactly what was promised. Code review with your CTO, external auditor, or trusted advisor is welcomed — encouraged, actually.

03

You own it

Live & maintained

It runs in your environment — your data, your controls, full audit trail. Source code, infrastructure, and data are yours outright: no black box, no lock‑in, no ransom on year two. Ongoing maintenance and iteration keep it sharp as your needs evolve.

What you'd otherwise hire$450k–$800k / yr, loadeda quant developer + data engineer + ops engineer, before benefits, equipment, recruiting, or management overhead

What a build costsFraction of one hire / oncescoped to your stage; the system keeps producing after the build is done

Sources: Built In, 6figr, Glassdoor, Levels.fyi, U.S. BLS — loaded compensation for senior data engineers, software engineers, and quantitative developers at fund‑adjacent firms.

05 /Why Us

A fund desk that builds — not an agency that read about finance.

We run what we build

We operate the kind of firm we build for. We know where the manual work hides — and what investment‑grade output looks like — because we ship to ourselves every day.

One principal, end to end

The person scoping your build is the one writing the code, integrating your data, and standing behind it. No juniors on your account, no account‑manager game of telephone, no offshoring.

Committee‑ready by design

Source‑traceable output with citations to the underlying documents. Built to stand up to an IC, an auditor, and a sceptical principal — not to impress in a demo.

Your data, your environment

It runs under your controls with a full audit trail. You own the source code, the data, and the infrastructure outright. No black box, no lock‑in, no positions touched.

06 /Who Builds It

You work directly with the person who built it.

Ryan Germain

I run Dark Matter, a systematic, market‑neutral digital‑asset fund. To operate it, I built the Dark Matter Terminal — a proprietary market‑intelligence system spanning equities, crypto, macro, and energy, fronted by a conversational analytical layer that surfaces cited, evidence‑based answers across markets.

Through Dark Matter Research & Development, I now build systems of that caliber for other firms. Many funds and family offices still run research, reporting, and market monitoring manually — because building the infrastructure properly means standing up a quantitative‑engineering team they can't justify. I deliver that capability directly: research pipelines, reporting automation, data integration, monitoring infrastructure, and execution and backtesting systems. Institutional capability without the institutional overhead.

Background in systematic‑trading infrastructure and quantitative finance, with a track record of architecting and shipping production financial systems end to end.

If your team is doing manually what well‑built infrastructure should handle, I'd welcome the conversation.

Start a Conversation

Tell us what your team is
doing by hand.

If a manual process is eating your team's weeks and a well‑built system should be handling it, that's the conversation. Bring the workflow; we'll diagnose where the time actually goes and what a build would look like. Tailored to your firm, no slide deck.

Hands‑on capacity is limited by design — one principal, one firm at a time

Runs in your environment Ownership source & data are yours Audit full trail, committee‑ready Delivery milestone‑gated

Prefer to talk? (514) 893-6399 · build@darkmatterrd.com

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