Newly opened to outside firms · Phase 1 launch Q3 2026

Institutional-grade
quant infrastructure.
Without building it yourself.

Valuation models, quant research, data integration, process automation, portfolio risk. By the team that built it for Cornerstone Investment Partners.

For two decades, this team built the quant and infrastructure stack inside one of Atlanta's premier alternatives firms. Running valuation, research, portfolio analytics, and risk infrastructure on behalf of institutional capital. In 2026, we're newly opening that practice to outside firms. Asset managers, hedge funds, family offices, and quant desks who need institutional-grade infrastructure without standing up the engineering team to build it themselves.

Schedule a consultation → See the credentials Bespoke engagements · NDA-first conversation
Institutional pedigree
25+ yrs
building quant + risk infrastructure for institutional capital
Team credentials
4
Wharton · McKinsey · IBM · Cornerstone Investment Partners
Global presence
4 cities
Atlanta · NYC · Toronto · Yerevan
Engagement model
Bespoke
retainer · project · embedded quant team
Capabilities · Five practice areas

Five areas where institutional firms outsource the build.

Every engagement starts from one of these five capability areas, sometimes two or three together. We don't sell shrink-wrapped software to institutional clients. We partner on bespoke builds and ongoing infrastructure, scoped from the underlying need.

Practice 01

Valuation models

DCF · LBO · NAV · third-party independent valuations

Bespoke valuation infrastructure tailored to your investment strategy and reporting requirements. Discounted cash flow models for credit and equity. LBO frameworks for private equity. NAV calculations for fund of funds and structured vehicles. IFRS / GAAP compliant outputs. Independent third-party valuations when required by your LPs or auditors.

DCFLBONAVComparablesMulti-currencyIFRS / GAAP
Practice 02

Quant research

signal development · backtesting · strategy validation

Custom signal development against your investment thesis. Backtesting infrastructure with realistic execution modeling, slippage, and capacity analysis. Strategy validation using walk-forward, Monte Carlo, and out-of-sample testing. Risk-adjusted return analysis with Sharpe, Sortino, Calmar, and bespoke metrics aligned to your investor reporting.

Signal developmentBacktestingWalk-forwardMonte CarloRisk-adjusted returns
Practice 03

Data integration

multi-source pipelines · Bloomberg · Refinitiv · alt data

End-to-end data pipelines across Bloomberg, Refinitiv, alt-data vendors, exchange feeds, and internal sources. Real-time and historical with quality monitoring, gap detection, and audit trails. Data warehousing on modern cloud infrastructure with point-in-time correctness, so your backtests don't quietly use information that wasn't available at the time.

BloombergRefinitivAlt dataReal-time + historicalPoint-in-timeCloud warehouse
Practice 04

Process automation

IM workflow · reporting · compliance · bespoke tooling

Investment management workflow automation. The operational layer between research and execution. Reporting automation for LPs, auditors, and internal stakeholders. Compliance automation with audit trails and regulatory framework support. Bespoke internal tooling that replaces spreadsheet sprawl with maintainable systems.

IM workflowLP reportingComplianceAudit trailsInternal tools
Practice 05

Portfolio & risk

attribution · scenarios · VaR · stress testing

Portfolio-level risk attribution. Where is your return actually coming from, and what risk are you taking to get it. Scenario testing against historical and synthetic market regimes. VaR analysis at the portfolio level with multiple methodologies. Parametric, historical simulation, Monte Carlo. Stress testing frameworks built for your specific exposure profile.

Risk attributionScenario testingVaRStress testingExposure analytics
The team · 25+ years institutional pedigree

Built by people who've shipped this before.

Arizet's institutional practice is led by the same team that built the quant infrastructure stack at Cornerstone Investment Partners over more than two decades. Running valuation, research, portfolio analytics, and risk for institutional capital across multiple market cycles. The team's pedigree spans Wharton, McKinsey, IBM, and Cornerstone, with deep operating experience in both finance and engineering.

The work we're now offering to outside firms is the same work we've been doing for institutional principals for years. Phase 1 of the external practice opens in Q3 2026, with selective engagements through 2026 and broader availability in 2027.

Pedigree · 01

Wharton

MBA-level credentials across leadership · finance + operations training

Pedigree · 02

McKinsey

Strategy consulting · operational excellence frameworks

Pedigree · 03

IBM

Enterprise systems · large-scale data + compute

Pedigree · 04

Cornerstone

Two decades building institutional quant + risk infrastructure

Engagement model · How we work

Four steps. Bespoke at every one.

Institutional engagements don't fit a template. The four phases below are the structure. What happens inside each phase is scoped to your firm, your strategy, and your existing infrastructure.

Phase 01 · 1-2 weeks

Discovery

NDA-first conversations. We learn your strategy, your existing stack, your operational gaps, and your investor reporting requirements.

Phase 02 · 2-4 weeks

Scoping

Detailed scope of work, deliverables, milestones, pricing. Fixed-price project, retainer, or embedded team. Your choice of engagement structure.

Phase 03 · 8-24 weeks

Bespoke build

Architecture, implementation, integration, testing, deployment. Weekly check-ins. Demos every 2 weeks. You see progress continuously, not just at the end.

Phase 04 · Ongoing

Maintenance

Retainer for ongoing support, feature additions, monitoring, and operations. Or hand-off to your team with documentation and training. Your choice.

From the blog · For institutional

Reading for the principal who builds and buys.

Long-form pieces on the economics of building vs. buying institutional infrastructure, the practical tradeoffs in quant research, and what we've learned across two decades of running this stack.

Outsourcing · 22 min

Why hedge funds are outsourcing quant infrastructure

The build-vs-buy math has shifted. What used to require a 12-person engineering team can now be outsourced to specialist firms.

Methodology · 18 min

Trading quality vs. P&L

Why measuring traders by P&L alone misses 70% of the signal. The 14 behavioral metrics institutional risk teams actually track.

Market structure · 24 min

The state of retail trading, 2026

Where retail flow is going, who's capturing it, and what that means for institutional liquidity providers.

Not what you're looking for?

Arizet builds across three customer pillars.

Build your quant edge
on proven infrastructure.

Phase 1 capacity is selective. Conversations begin with an NDA. Engagements scoped to the underlying need, not packaged into shrink-wrapped software.