Previous Projects

MICHAEL WIBRACHT

Founder & Principal, AllDark.Horse

San Antonio, Texas

Twenty-five years underwriting, capitalizing, and building real estate. Now building the software that work should have had.

OVERVIEW

Michael Wibracht is a real estate developer turned AI solutions architect. Over 25 years he co-founded and led 210 Development Group and Mission DG, where he served as Co-Founder, Managing Partner, and President and drove the strategy, capitalization, and execution of market-rate and affordable multifamily, mixed-income and mixed-use development, for-sale residential, adaptive reuse, urban infill, and complex public-private partnerships across Texas — more than $1 billion in construction and development, and over 6,000 residential units delivered or in the pipeline.

He holds a BBA in Management Information Systems from Texas A&M University, College Station. That combination — a systems education and a quarter century of closing capital-intensive, multi-source transactions — is the whole premise of what he does now.

Through AllDark.Horse, his AI solutions studio, Michael designs and operates purpose-built AI financial and design tools for real estate development finance across the full product spectrum: market-rate rental, affordable and mixed-income, for-sale residential, adaptive reuse, and commercial and mixed-use. The tools are not adapted from generic software. They were specified by someone who has personally sized the loan, defended the basis, and signed the guaranty.

WHY ALLDARK.HORSE EXISTS

Development finance is not hard because the math is hard. It is hard because the math lives in forty places at once — a lender's term sheet, an equity pricing letter, a construction budget, a rate that moved this morning, an architect's drawing that has not been reconciled to the rent roll or the price list — and because a single assumption drifting out of date can quietly invalidate an entire capital stack weeks before anyone notices.

That is true of a 300-unit market-rate podium deal, a for-sale townhome community with a unit-release schedule, and a four-layer LIHTC historic adaptive reuse alike. The sources differ; the failure mode does not.

Generalist AI platforms cannot solve this. They do not know that 221(d)(4) amortizes over 40 years and prices differently for market-rate than for a high-rental-assistance property, that the applicable fraction is not the same as the qualified basis, that a construction loan's interest reserve is a function of the draw curve, or that absorption assumptions drive a for-sale pro forma the way rent growth drives a rental one. Specialists in this industry, meanwhile, have historically been armed with spreadsheets and institutional memory.

AllDark.Horse is built at that intersection: software with the domain judgment of an operator encoded into it.

DEVELOPMENT TRACK RECORD

- $1B+ in construction and development overseen

- 6,000+ residential units delivered or in development

- $405M total development investment

- $140M in historic adaptive redevelopment

- $114M LIHTC eligible basis

- $31M in Federal Historic Tax Credit equity

Product experience spans market-rate and workforce multifamily, affordable and mixed-income rental, senior housing, for-sale residential, mixed-use, and historic adaptive reuse — garden, wrap, podium, mid-rise, and conversion product.

Transactional experience spans HUD 221(d)(4) and 223(f) across market-rate, middle-income, affordable, and rental-assisted tiers; Fannie Mae DUS and Freddie Mac; bank and bridge construction debt; LIHTC (4% and 9%); Federal and State Historic Tax Credits; New Markets Tax Credits; and joint-venture and preferred equity structures.

THE PLATFORMS

AllDark.Horse operates a suite of AI-powered intelligence platforms purpose-built for real estate development finance and design. Four have been filed with the U.S. Patent and Trademark Office as provisional patent applications (April 2026), covering 101 claims across multi-source data pipelines, automated underwriting, architectural layout generation, and cost estimation. The ALLDARK.HORSE and DIGITAL TWIN ENGINE trademarks are pending.

The platforms are asset-class agnostic by design. Affordable and adaptive reuse deals are the hardest case — the most capital sources, the most compliance constraints, the most ways to be wrong — so the systems were built to that standard and run market-rate and for-sale product on the same engine.

Digital Twin Engine — the pipeline that re-underwrites itself

The problem: a deal underwritten in March is a work of fiction by June. Rates move, spreads move, sources open and close, and nobody re-runs the model until something has already gone wrong.

What it does: Digital Twin Engine is the unifying platform layer — live pipeline intelligence with FRED API rate integration, automated daily re-underwriting, viability scoring on a 0-100 scale, and tiered email alerts when a deal's position materially changes. A FastAPI REST backend (12 endpoints) and React dashboard expose sensitivity analysis and full capital-stack modeling: conventional and HUD-insured debt, construction and bridge facilities, joint-venture and preferred equity, and — where applicable — a layered soft-source gap filler covering deferred developer fee, PBV, HOME, CDBG, TDHCA, local gap/TIF, FHLB AHP, and NMTC. Containerized, with automated rate cycles, weekly Excel exports, and SSL-secured multi-tenant deployment.

Why it matters: the portfolio tells you when it has changed, instead of waiting to be asked. That applies to a market-rate refinance watching its rate lock window as much as it does to a nine-source affordable deal.

Nirmata Core — from drawing to cost schedule, without the takeoff

The problem: the gap between a set of construction documents and a defensible development budget is measured in weeks of manual takeoff, and it has to be re-crossed every time the unit mix or product type changes.

What it does: Nirmata Core ingests DWG/DXF natively, converting construction documents into structured building geometry with no manual takeoff. From that geometry it generates code-compliant residential layouts — rental units, for-sale plans, and loft mezzanines — detailed interior plans for every unit or plan type on every floor, and dual-format construction cost estimates that produce a development cost schedule and a CSI MasterFormat division breakdown from a single computation. The same geometry drives market-rate, for-sale, and LIHTC-format outputs; only the reporting layer changes.

Why it matters: the architecture and the capital stack stop being two separate exercises that have to be reconciled by hand — whether the output is a rent roll or a price list.

The Kasati — deal sourcing with provenance

The problem: the opportunities worth finding are buried in government parcel records, federal overlays, and foreclosure notices that do not speak to each other, and most tools that claim to aggregate them are scraping their way toward a cease-and-desist.

What it does: The Kasati is an authenticated multi-source opportunity pipeline surfacing development and redevelopment targets — infill sites, underused and vacant buildings, conversion candidates, and portfolio acquisitions — from government parcel records, federal overlays (QCT / DDA / Opportunity Zone), tax foreclosure notices, and market listings. Records are fused across sources via normalized-address fingerprinting with per-attribute source provenance preserved, then scored against a multi-dimensional viability rubric that can be tuned to market-rate, for-sale, or affordable criteria.

Why it matters: every field in a Kasati record can be traced to the source that produced it — and the platform operates exclusively on authenticated APIs and user-initiated data transfers. No scraping. No terms-of-service violations.

FOUNDATIONAL FINANCIAL MODELS

The platform layer sits on a base of individually validated models:

- 10-Year Treasury Predictor with HUD Pricing — automated daily FRED pull, three-model forecast engine (momentum, mean reversion, volatility-adjusted), calibrated HUD 223(f) and 221(d)(4) spreads, weekly email delivery

- HUD 223(f) Loan Sizer — DSCR-constrained mortgage sizing for acquisition and refinance across market-rate (87% LTV / 1.15x), affordable and middle-income (90% / 1.11x), and rental-assisted tiers, with current MIP at a uniform 25 bps per FR-6522-N-02, plus LTV caps and debt yield analysis

- HUD 221(d)(4) Loan Sizer — new construction and substantial rehabilitation: 40-year amortization, tier-specific DSCR and loan-to-cost constraints, and construction-period interest modeling

- LIHTC Financial Model — full 4% and 9% underwriting with eligible basis calculation, applicable fraction, 10-year credit stream, investor pricing, Texas State LIHTC (HB 1058) layer, and TDHCA-format Development Cost Schedule

- Fannie Mae Small Loan Sizer — side-by-side Freddie Mac SBL and Fannie Mae comparison with LTV/DSCR constraints and rate lock analysis

HOW THE WORK IS BUILT

Four commitments govern every platform AllDark.Horse ships:

Provenance over convenience. Every data point carries its source. Fused records preserve per-attribute origin so a number can always be defended, not just displayed.

Authenticated sources only. Government APIs and user-initiated transfers. No scraping, no gray-area acquisition, nothing that creates exposure for the client downstream.

The operator stays in the chair. These tools produce underwriting, layouts, and estimates fast enough to change how a pipeline is run — and they are built to be checked. Assumptions are surfaced, not buried.

Domain fidelity first. A model that is elegant and wrong about a DSCR tier or an applicable fraction is worthless. Correctness against the actual regulatory and credit framework precedes everything else.

WORKING WITH ALLDARK.HORSE

For developers and builders — platform access, custom model development, and pipeline intelligence built around an existing portfolio and deal criteria, across rental, for-sale, and mixed-use product.

For lenders, syndicators, and capital partners — underwriting and screening tools calibrated to specific credit boxes, program requirements, and asset classes.

For principals and joint-venture partners — direct development expertise on ground-up multifamily, adaptive reuse, historic credit, and layered transactions.

TECHNICAL DETAIL

Stack: Python (FastAPI, pandas, NumPy), React/JavaScript, REST API design, Docker containerization, OAuth 2.0 authentication, FRED API integration, automated email delivery, nginx reverse proxy with SSL, cron-based scheduling, PostgreSQL, libredwg and ezdxf for CAD pipeline ingestion, full-stack cloud deployment on DigitalOcean/Ubuntu infrastructure.

Domain specialization: AI-powered underwriting and design automation across market-rate multifamily, workforce and middle-income housing, affordable and mixed-income rental, for-sale residential, senior housing, mixed-use, and adaptive reuse. Financing structures include HUD 221(d)(4) and 223(f) across all property tiers, Fannie Mae DUS and Freddie Mac SBL, bank and bridge construction debt, LIHTC (4% and 9%), Federal and State Historic Tax Credits, New Markets Tax Credits, Project-Based Vouchers, and layered public capital including HOME, CDBG, TDHCA soft debt, FHLB AHP, TIF/TIRZ, and seller financing.

PROFESSIONAL STANDING

Mr. Wibracht maintains full eligibility to participate in federally related and regulated transactions and is not suspended, debarred, or restricted from engaging in projects involving institutional or government-related capital.

CONTACT

AllDark.Horse

San Antonio, Texas