Dark Matter · R&D. Bespoke infrastructure for serious financial firms.

01 /The Problem

Bespoke workflows. Custom data. The systems vendor platforms can't reach.

Every serious financial firm carries the same gap, from a single family office to a multi billion dollar asset manager, from an accounting practice to an insurer: workflows too specific for off the shelf platforms and edges too proprietary to hand to a consultancy. Custom data layers across custodians, prime brokers, and fund admins. Diligence that demands forensic depth on every deal. Monitoring infrastructure tailored to the actual mandate. Internal tools the firm runs on but never had time to build properly.

The work is automatable. Building it properly means standing up a dedicated quantitative engineering function: a senior hire, a manager, and a stack that has to be supported in perpetuity. Most firms don't carry that weight, so the work stays manual and the firm's best people spend their weeks rekeying data instead of making decisions.

$1.4T

in asset-manager IT spend industry-wide, and the bespoke layer keeps growing, not shrinking

~70%

of asset managers cite tech debt and system integration as their top operational blocker

57%

of family offices cite a lack of internal technology expertise as their #1 barrier

Months

a single mandate, direct deal, or fund launch can absorb without dedicated infrastructure

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

02 /What We Build

Bespoke systems, scoped to the workflows that matter most.

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 your models actually need.

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
Machine-learning signal & forecasting models
Conversational analytical layer over your data

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.

Loaded cost of building it in-house$900k–$1.6M / yra realistic team for this work: senior quant developer + senior data engineer + ops engineer, fully loaded (base, bonus, benefits, payroll taxes, equipment, management overhead). A single senior quant developer alone runs $450k to $800k loaded.

A scoped build, end to endFraction of one FTE / oncedelivered in weeks, fully owned by you afterward, runs without supervision. The same outcome a multi-year in-house buildout would produce, without the recruiting cycle or the multi-year ramp.

Compensation sources: eFinancialCareers quant compensation report 2025; Wall Street Oasis hedge fund pay guide; Glassdoor (NYC senior data engineer, NYC SRE/DevOps); Levels.fyi (fintech software engineer). Loaded figures apply standard 1.3–1.4× cash-comp multiplier for benefits, payroll taxes, equipment, and management overhead.

What you walk away with

Working system in your environment Full source code in your repo Integration tested against your live data Architecture & runbook documentation Training session for your team Mutual NDA + audit trail

05 /vs The Alternatives

Stack us against what your firm would otherwise do.

A sceptical buyer's mental matrix, drawn explicitly. Pick the column that fits.

Off-the-shelf platforms
(Addepar, Eton Solutions, Asora, Sage)

Big consulting
(Accenture, Deloitte, EY)

In-house hire
(quant dev + data eng + ops eng)

Dark Matter R&D
Custom build, you own it

Cost

$12–60k+/yr forever, per seat scaling

$500k–$5M+ per engagement, partner-rate

$450k–$800k/yr per senior quant eng; team of 3 ≈ $900k–$1.6M/yr

Scoped to the build. A fraction of any of these, then it's yours

Fit to your workflow

Generic. You bend to it

Custom, but slide-heavy

Custom, if they stay

Custom. Scoped to you, on your data

Time to value

Months of onboarding

6–18 months

6–12 months to hire, then ramp

Weeks, milestone-gated

Who builds it

Vendor PM + global support

Team of juniors, partner sells

Whoever you can hire

A fund operator. End to end.

Ownership

Vendor lock-in, your data on their cloud

Deliverables + ongoing dependency

Yours, and the key-person risk

Source & data fully yours, in your environment

What happens year 2

Renewal invoice

Statement of work #2

Salary + benefits + bonus

It keeps running. Optional retainer if you want changes.

06 /Why Us

A fund desk that builds. Not an agency that read about finance.

We run what we build

We operate a live trading desk. We know what investment-grade output looks like, where the integration debt actually accumulates, and what survives an IC, an auditor, and a Monday open. 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.

07 /Who Builds It

You work directly with the person who built it.

Ryan Germain

Founder & Principal Engineer

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 investment and financial firms: hedge funds, asset managers, private credit and PE shops, family offices, RIAs, accounting and insurance firms, banks, and fund administrators. Every serious firm carries a bespoke layer that vendor platforms don't reach and consultancies won't ship: research pipelines, reporting automation, data integration, monitoring infrastructure, execution and backtesting systems. I deliver that layer directly, end to end, on the firm's own data and in the firm's own environment.

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.

08 /Frequently Asked

Anticipating the obvious questions.

If your IC, CTO, or compliance officer would ask it, it's probably below.

Where does our data live?

Your environment. AWS, Azure, GCP, on-prem. Your account, your VPC, your controls. We never hold or move your data into a vendor cloud. Mutual NDA on every engagement, signed before the scoping sprint.

What if you get hit by a bus?

You have the full source code and documentation in your repo from day one. A qualified engineer can pick up where I left off without me. No black-box hosting, no proprietary runtime, no lock-in.

Do we need a CTO to maintain it?

No. The system runs unattended. For changes or extensions, you can either retain me at a flat monthly rate, hand it to your team, or hire a freelance engineer. Your call. Most clients pick the retainer because it's cheaper than one developer day.

Why not just buy Addepar / Sage / Eton Solutions?

Because off-the-shelf platforms force your workflow to fit their schema, charge you in perpetuity, and don't extend to the messy edges (your bespoke statements, your custom diligence, your specific monitoring). If a platform fits, use it. If it doesn't, the manual work isn't going away, and that's where I come in.

How is this not just another "AI consultant"?

I'm not packaging a generic LLM behind a chatbot. The Terminal, and what I'd build for you, is purpose-built infrastructure where AI is one layer over a deterministic, source-traceable engine. Every claim cites the underlying document or data point. The output stands up to an investment committee.

What's the typical engagement size?

Scoping sprints are a fixed $7,500. Builds scope from focused single-workflow systems through full data-layer rollouts and multi-system, enterprise-scale infrastructure. The scoping sprint produces a written spec with a fixed quote on the build. You decide on a known number, not an open meter.

What language and stack?

Python is the workhorse for data, machine-learning, and quantitative work; C++ / Rust appear in performance-critical paths (execution, tick-level signals); TypeScript / React for any UI. We pick the tool that fits the job, not the other way around, and every choice is documented so your team or a successor can read the code.

Will you sign our paper?

Yes. Mutual NDAs, MSAs, your DPA. I'm comfortable with code review by your CTO, an external auditor, or a trusted technical advisor. I'd rather you verify it than take my word for it.

◆ Engagements we'd decline

Anything that requires us to hold, custody, or trade your assets
"Build us an AI hedge fund from a YouTube tutorial"
Generic CRM, HR, or marketing automation outside finance
Greenfield SaaS MVPs unrelated to the buyer's existing book
Pure advisory or PowerPoint engagements without a shipped artifact
Anything we wouldn't ship to ourselves

Start a Conversation

Where vendor platforms end,
we begin.

Bring the workflow, data layer, or analytical capability your firm needs but can't buy off the shelf. The conversation is a working diagnostic: what a purpose-built system would look like on your data, in your environment. Substantive and direct. No slide deck.

Engagements taken selectively. Principal-led, in sequence, on the work that matters

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

◆ Start a build

Book a working callBring the workflow. We confirm within the day →

or send a brief