Full-Stack Platform Engineering · IPS-Builds.com

We build the platform. You run the business.

We build custom CRMs and operational tools tailored to your exact business. Every data source you have — pulled into one system, surfaced with AI, and acted on by agents that do real jobs inside your platform. Digital labor, built in.

4
Live platforms shipped
~74%
Fight prediction accuracy (holdout)
8 min
vs 3-day human research dossier
$0
Vendor infrastructure dependency
What we build

Three things we do
better than anyone.

Every engagement starts the same way: your data is scattered, your workflow doesn't exist in any product, and you're paying people to do things a machine should do. We fix all three.

Data Platform Engineering

We scrape unstructured data, normalize it across conflicting schemas, and build a proprietary database you own outright. No third-party data feed, no subscription that disappears.

  • Multi-source aggregation pipelines
  • PostgreSQL / Supabase architecture
  • Cross-source normalization & scoring
  • Automated refresh & sync

Custom Software & CRM

Vertical-specific applications built around your actual workflow. Not a generic SaaS with your logo on it. Software that does exactly what your business does, and nothing else.

  • Multi-tenant SaaS architecture
  • Custom CRM & dashboard builds
  • HIPAA-compliant architecture
  • Static HTML + Supabase + Vercel

AI Agents & Digital Labor

We build AI agents that do actual jobs inside your system — not a chatbot, not a dashboard. Agents that research, respond, score, route, and act. Digital workers embedded in your platform.

  • Agents that monitor & take action 24/7
  • AI research & dossier pipelines
  • ML scoring & prediction engines
  • CRM-embedded agent workflows
How we actually build

Raw data → live platform.
Here's every step.

Click any step to see what we do, how we do it, and a real example from a live platform. This is the IPS build process — made visible.

Our work

Four platforms. All custom. All live.

IPS owns and operates four distinct products across as many industries. Click any to explore the build.

Sports / ML ★ Featured Platform

MMAmodel.ai

mmamodel.ai
🥊

The only publicly available UFC analytics platform combining a proprietary fight database, a 4-dimensional rating engine, a 5-model stacked ML ensemble, and LLM-generated fight narratives. IPS built and owns the entire stack — data pipeline, ratings engine, ML training infrastructure, prediction API, and the consumer-facing website. ~74% prediction accuracy on holdout validation.

~74%
Prediction accuracy
8,500+
Fights in DB
5
ML models (stacked)
Weekly
Auto-retraining
5-Model Stacked Ensemble — each trained independently
LightGBM
88%
XGBoost
85%
CatBoost
84%
Logistic Regression
78%
Siamese NN
81%
Meta (stacked)
~74%
Proprietary DB 4D Elo/Glicko-2 Temporal CV (no leakage) GitHub Actions retrain FastAPI + Railway Claude narratives Betting value engine
What a prediction looks like
UFC 308 · Championship LIVE MODEL OUTPUT
Makhachev 73.4%
vs
Oliveira 26.6%
Model: -275 · Market: -280 — NEUTRAL, market agrees
Poirier 61.2%
vs
Gaethje 38.8%
Model: -158 · Market: +130 ★ EDGE — market disagrees
4-Dimensional Elo — Islam Makhachev
Overall Elo
2,341
Grappling Elo
2,489
Striking Elo
2,110
Finishing Elo
2,240
Betting value engine: When the model's implied odds diverge from the market by 10%+, it surfaces a ★ EDGE signal. That's the actual product — not the prediction, but finding where the market is wrong.
Industries we serve

If it happens behind a screen,
we can build it.

Bring us your data — structured, unstructured, or nonexistent. We've operated in regulated, gray-market, high-compliance, and gray-area industries. No vertical is out of scope.

Healthcare & Medical
HIPAA ready PHI compliant

HIPAA-ready from day one. Audit logging, RLS, auth-gating designed in — not retrofitted.

Patient portals, clinical data platforms, medical device dashboards. PHI access logging, field-level encryption, RBAC enforced at the database layer with PostgreSQL RLS. Custom EMR data integrations. A breach in healthcare is a legal event — we architect for that from the first migration.
Cannabis & Gray Market
Live product Carrier-grade SMS

We built the telecom stack when carriers said no. StickySignal and the infrastructure behind it are ours.

When standard SMS carriers and platforms blocked cannabis clients, we built our own carrier-grade provisioning stack from scratch — direct agreements, no Twilio, no Bandwidth. StickySignal runs on this today. We know how to build in industries where the rules are unwritten and platforms can pull the rug.
Government & Public Sector
Live product Federal data

Six federal datasets cross-referenced and scored. GovGreed is a live example of government data engineering at scale.

STOCK Act disclosures, Congress.gov, FEC, Senate LDA, USASpending, market cap data — all normalized, bridged, and scored in real time. 157,770 predictions across politician × bill combinations, running in ~30 seconds inside PostgreSQL. No Python. No model files. Just a well-designed schema.
B2B Enterprise & Sales
Live product $75K/yr enterprise

10+ parallel data sources per job, AI synthesis, fully-written executive dossiers in 8 minutes.

Lead Detective pulls from LinkedIn, SEC EDGAR, Crunchbase, Google News, Glassdoor, and our proprietary business database simultaneously. Premier AI models with deep vendor relationships synthesize everything into a dossier, account plan, and conversation guide — in prose, not bullet dumps. Enterprise pricing: $75K/year. ROI documented at 85–120x.
Sports & Performance Analytics
Live product ~74% accuracy

We built the only publicly available UFC prediction platform that owns its data, ratings engine, and ML pipeline.

mmamodel.ai: 8,500+ fights, 70,000+ stat records, a 4-dimensional Glicko-2 rating engine, 5-model stacked ML ensemble that retrains weekly via GitHub Actions. Any sport with structured outcome data is a candidate. We've done the hardest version.
Finance & Fintech
STOCK Act data ML scoring

Financial data pipelines, trading pattern analysis, ML scoring, and compliance-aware architectures.

SEC filings, FEC contributions, market cap data, historical trading records — we know how to pull, normalize, and score financial data at scale. Compliance-aware from the schema level: audit trails, immutable records, access controls built in.
Data-Heavy Any Vertical
Scraping included Any source

Have data but missing pieces? We go get it. Web, government portals, APIs, PDFs — all structured and loaded.

Our scraping infrastructure covers LinkedIn, SEC, government portals, news APIs, financial databases, and custom targets. If the data exists on the public web or behind a permissive API, we extract it, normalize it, and load it into your database on a schedule. Raw archive kept so you can reprocess without re-scraping.
Custom / Any Vertical
Any industry We adapt

If it happens behind a computer screen and involves data, logic, or automation — we've built something like it.

We don't have a template we shoehorn clients into. Every engagement starts with a data audit and architecture session. Healthcare? Done. Legal? Done. Real estate? Done. Industrial IoT? Done. The stack adapts — PostgreSQL, custom scraping, AI agents, ML models, telecom — whatever the vertical requires.
Why IPS

Nobody matches
our speed.

First call to MVP in 30 days. If it happens behind a computer screen, we build it — faster than anyone, with full ownership at every layer.

30
days
First call → MVP
4
live platforms
We own & operate
6
stack layers
Infra to telecom
verticals
No industry too complex
Capability IPS Dev Shop Big Agency
First call → MVP ~30 days 3–6 months 6–18 months
Owns the data pipeline
Custom ML models (not wrappers) subcontracted
Carrier-grade telecom
Clean handoff — docs, infra access, your data sometimes
Gray market / regulated industries case by case
Live products in production today 4 platforms client work only client work only
Full Stack Ownership

We own the stack. Every layer.

Most agencies own the application layer and subcontract the rest. We own from infrastructure to telecom.

Application
Custom dashboards, CRMs, analytics platforms, AI interfaces
React, Next.js, vanilla JS, Flutter mobile. Static-first architecture on Vercel — no server to maintain, no scaling surprises. Every frontend we build can be handed to any developer.
AI & Intelligence
In-house ML engineering · Custom models · Database-native AI
Our ML engineer holds a master's in machine learning and owns every model in production. We don't wrap APIs and call it AI — we design the architecture, build the training pipeline, and deploy custom models. GovGreed scores 157K predictions inside PostgreSQL stored functions. mmamodel.ai runs a 5-model stacked ensemble (LightGBM, XGBoost, CatBoost, Logistic Regression, Siamese NN) that retrains automatically every Monday. We are database architects first — the AI lives in the data layer, not bolted on top.
Data Layer
PostgreSQL on hardened Supabase forks, custom schemas, row-level security
We own the database from day one. Custom migration files, schema documentation, RLS policies enforced at the database level. We've forked and run custom Supabase instances when clients need behavior the standard stack doesn't support. Your data never lives in a system we rent from a third party we don't control.
Data Collection
Web scrapers, government APIs, SEC, LinkedIn, 10+ source types
If the data exists somewhere, we extract it. Scheduled pipelines pulling from government portals, SEC EDGAR, LinkedIn, Crunchbase, financial APIs, news feeds. Raw archive kept before normalization so reprocessing is always possible. GovGreed: 6 federal datasets. Lead Detective: 10+ parallel scrapers per job. mmamodel.ai: 8,500 fights built from scratch.
Telecom / Communications
★ Unique
Carrier-grade SMS provisioning. Direct agreements. No Twilio, no Bandwidth.
When a gray market client needed SMS campaigns that no standard platform would touch, we built the entire telecom stack from scratch: carrier provisioning, number management, delivery routing, compliance scaffolding. We hold direct carrier relationships. StickySignal runs on this today. If your industry has carrier-level restrictions — cannabis, finance, healthcare — we've already solved it.
Infrastructure
Vercel, Railway, Cloudflare, custom domains, CI/CD
We deploy on commodity infrastructure you own directly: Vercel for frontends, Railway or Render for APIs, Cloudflare for DNS and edge. GitHub Actions for CI/CD. No proprietary IPS runtime. Every piece is one you can operate independently after handoff.
Let's build

Tell us what
we're building.

30-minute discovery call. We'll tell you exactly how we'd architect it, what it costs, and how long it takes. No pitch deck. Just the honest technical answer.

No RFP required. No scope doc. Just a conversation.