XGInfoTech
AI-native software engineering

We build software with AI in the loop — the methodology that earns the cost reduction.

Custom software, data platforms, dashboards, agentic bots, AI features — built by a senior team that uses Claude Code, OpenAI Codex, and the rest of the modern AI stack under a methodology we evolved across 30+ years and proved by shipping XGAIMS, our own AI Marketing ERP.

No discovery decks. We scope, ship the first slice, then iterate.
30–50%
Lower software build cost vs. traditional outsourced delivery
2–3x
Faster delivery on well-scoped work
30+ years
Combined experience across software, data, and AI
XGAIMS
Built and run by us — proof of methodology

Delivery figures reflect industry research on AI-assisted development (McKinsey, MIT/GitHub, DORA 2024–25) and our own engagement data. Outcomes vary by codebase, scope clarity, and stack — see where the numbers fit best.

Selected clients · 30+ years of work
New York Life
Wells Fargo
American Express
Southern California Edison
City of Phoenix
Arizona Supreme Court
Team Health
Hach
What we build

One discipline. Nine capabilities.

Generalists by design — full-stack web, mobile, backend, AI, data, integrations, dashboards, agentic bots, and the unglamorous infrastructure that keeps systems alive after launch.

Data integration, ETL & connected systems
Data modeling & analytics
ML & predictive systems
Custom AI applications
Dashboards & analytics surfaces
Agentic bots & assistants
Full-stack web & mobile
Modernization & cloud
Monitoring & maintenance
How we work

The methodology, in four steps.

AI generates code fast. AI under a senior-led, spec-driven, test-first, eval-gated loop generates production-grade code at 30–50% lower cost. The discipline is the difference.

1
Spec-driven
A written spec is the source of truth. AI generates code from it; humans iterate the spec, not the keyboard.
2
Test-first (ATDD)
Given/When/Then before code. Tests are the verifiable target the AI works against — not a hope after the fact.
3
Senior review
Every AI-generated change goes through a senior engineer. This is the step that protects stability — DORA data is unambiguous.
4
Eval & safety gates
Automated quality and hallucination checks before merge. The gating that protects XGAIMS in production protects your code.
Try us with a small project first

First Build · 4 weeks · capped at $20K

One concrete deliverable — dashboard, integration, agentic bot, or app slice — shipped end-to-end under the full methodology. You get the code, the methodology in action, and a senior team who's already worked with you when you're ready to scope something larger.

Proof that the methodology works

We built XGAIMS this way.

XGAIMS is our AI Marketing ERP — a multi-tenant production platform with predictive ML, agentic workflows, hallucination-grounded LLM features, real-time CRM bidirectional sync, and a closed-loop feedback system. Built by a small senior team using the exact methodology we apply to client engagements. If you want to know what we can ship, look at what we ship for ourselves.

  • Production at real scale. Multi-tenant, real customers, real LLM cost discipline.
  • The same loop end-to-end. Spec → ATDD → AI generation → senior review → eval gates.
  • Real ML, real integrations. Predictive segmentation, channel/budget recs, CRM sync, agentic workflows.
What we shipped on XGAIMS
  • Multi-tenant React / Next.js front-end with 50+ admin surfaces
  • Python services orchestrating 20+ background jobs across LLM, ML, ETL
  • Bidirectional CRM sync (HubSpot / Salesforce / Pipedrive)
  • Hallucination gate over LLM outputs — grounded numbers + quote attributions
  • Real-time chat inbox with operator handoff at autonomy ceiling
  • Cal.com adapter with auto-deal creation in CRM

Have a software problem worth solving?

Tell us what you're trying to ship. We'll come back within one business day with a scope, a timeline, and the team who would build it.