Est. MMXXIV · Hermosillo, MX 29.0729° N · 110.9559° W
3 slots · Q3 2026

We build
the app.
Exclusively.

An exclusive app development studio. Idea to production, engineered end-to-end. Built to run, not to demo.

SYS
15+yrcombined exp.
40+apps shipped
No.001

Now.

Workshop log · Updated weekly
01BuildingAn infrastructure provisioning agent — natural language to live Fly.io stacks in under 90s. Hard part is validation before apply.May 2026
02EngagedEmbedded technical lead for a Series B platform — system design and AI lab. Multi-agent eval harness, ADR-driven architecture governance.Ongoing
03ShippedModel router v2 — privacy overrides, per-workload routing, fallback chains. 40K+ req/day at <12ms routing overhead.Apr 2026
04ReadingDesigning Data-Intensive Applications ch. 11 · Anthropic interpretability papers · Anyscale on LLM serving economics.This month
05WritingNew note — The $50K AI budget mistake. Demo-to-production mismatch. Architecture conversation that should happen in week one.In draft
No.002

Selected work.

40+ apps shipped
001

Radian Corporation — AI Pricing Engine

Previous POCs collapsed at concurrency. Rebuilt the infra layer — routing, caching, eval harness, observability on day one. Production from week one.

InsuranceFastAPIClaude APIpgvector
500msp95 latency
94%accuracy
99.8%uptime

Context

HomeGenius needed a high-throughput pricing API serving thousands of simultaneous broker requests — each requiring real-time home value calculations across multiple risk and market factors.

What we built

Rebuilt the infra layer from scratch: async request routing over AWS SQS to decouple broker intake from model inference, pgvector-backed semantic caching to skip redundant calculations on similar inputs, and a factor-based pricing engine that accounts for property characteristics, location signals, and market conditions. Full observability from day one.

Stack

FastAPI · Claude API · AWS SQS · pgvector · PostgreSQL · CloudWatch

002

SaaS Platform — AI Infra Provisioning

Natural language to live Fly.io + Docker Compose stacks in under 90 seconds. Validation layer before apply. Self-healing loop handles 94% of runtime issues autonomously.

InfrastructureFly.ion8nAgents
<90sprovisioning
−87%devops hours

Context

An AI-powered cloud platform for infrastructure provisioning. Teams describe what they need in plain language — the system handles the rest, from config generation to deployment to self-healing.

What we built

Natural language input → LLM-generated cloud configs → validation layer (dry-run + schema check) → live deployment in under 90 seconds. A self-healing agent monitors runtime health and resolves ~94% of issues autonomously — restarts, config drift, resource limits — without human intervention.

Stack

Fly.io · Docker Compose · n8n · Claude API · GitHub Actions

003

Shun Technologies — Unified Vendor Experience

Unified chatbot and workflow platform for supply chain operations. Bottler and mounting automation, ML-driven demand signals, and vendor management in a single interface.

Supply ChainMLChatbotWorkflows
−18%stockouts
−23%holding cost

Context

Supply chain operations spread across disconnected tools — vendors, bottlers, and mounting operations each with their own systems. No single view of demand, inventory, or supplier status.

What we built

Unified vendor experience platform: a conversational interface for operations teams to query inventory, trigger workflows, and surface ML-driven demand signals. Bottler and mounting automation reduced manual coordination overhead significantly. Integrated directly with WMS and ERP systems.

Stack

Python · ML ensemble · LLM chatbot · REST · PostgreSQL · WMS/ERP connectors

004

UniTravel Tech — Dynamic Pricing for Tourism

Sub-100ms pricing API for 50K+ daily requests. ML demand forecasting, competitor rate signals, and yield management across 12 LATAM tourism markets.

TravelTourismReal-Time PricingYield Management
+14%revenue lift
<100msp99 latency

Context

Tourism marketplace competing across 12 LATAM markets where pricing windows are narrow and competitor rates shift intraday. Static pricing was leaving margin on the table.

What we built

Sub-100ms pricing API backed by a caching layer over ML demand forecasts. Competitor rate feeds drove a yield management model adjusting prices every 15 minutes per market. Rolled out market-by-market with an A/B harness to validate lift before full deploy.

Stack

FastAPI · Redis · ML ensemble · PostgreSQL · competitor rate feeds · AWS

No.003

Notes & field reports.

Production-first · One per week
No.004

Building in public.

Open source · Tools we use daily
No.005

Newsletter.

Field notes · Every Friday
Systec Field Notes

One note per week. Real problems, real code.

Not a newsletter about AI in general. A dispatch from inside production systems — what broke, what shipped, what we'd do differently. Operators and founders only.

No noise. Unsubscribe any time. Sent every Friday.
✓ TRANSMITTED

You're in. First issue Friday.

Check your inbox for a confirmation — sometimes lands in spam.
4Issues out
~5minAvg read
FriEvery week
Latest issue
The model router problem — privacy, fallback, and trust
No.006

Work with us.

Direct · Honest · Fast intake

Two paths in. One conversation either way — no pitch decks, no discovery forms.

SYS
Systec
Exclusive App Development Studio

If you have an idea and a budget: we scope it as a fixed build — timeline, cost, and deliverable defined before we start. Idea to production, engineered end-to-end.

If you're earlier — exploring, validating, deciding whether to build at all — just write. One paragraph. Forty-eight hour reply.

Path AAI Readiness SprintTwo weeks · Report · Debrief.
Path BJust writeOne paragraph · 48-hour reply.
Path CFractional CTOOngoing builds · Architecture · AI lab.
AgenciesPartner programWhite-label delivery · Request brief.
Built by Systec.
Hermosillo · Sonora · México · MST