MODULE 05.1 — SERVERLESS BACKENDS
Scale-to-zero cloud logic
Event-driven microservices on AWS-grade primitives. Capacity follows demand in both directions — burst absorption for API spikes and imports, zero compute spend at rest.
JINTECH — SYSTEMS ENGINEERING · GERMANY
Engineering the cloud
you own.
Native mobile applications, serverless cloud platforms and hardened AI pipelines — delivered with the rigor of an audit and the pace of a product team. One partner, the whole stack.
THE STANDARD
Built on audited ground.
Trust should be verifiable, not claimed. We build on infrastructure that passes the industry's strictest independent audits — and we run our own work the same way: every change tracked in version control, access granted only where needed, every release reviewed and reproducible.
The result is a stack where compliance is not a quarterly scramble but a property of the architecture — from the region your data lives in to the cipher suite it travels on.
Credentials shown are held by our infrastructure partners — selected precisely for their security and compliance posture.
ISO/IEC 27001
Information-security management — certified at our hosting and cloud providers.
SOC 2 Type 2
Continuously audited operational security — attested at our infrastructure providers.
EU-U.S. DPF · SCCs
GDPR-compliant data transfers — our providers are certified under the EU-U.S. Data Privacy Framework.
NATIVE MOBILE ENGINEERING
Native, because your users can tell.
Cross-platform shortcuts show up where it hurts: frame drops, battery drain, rejected releases. We build Swift and Kotlin applications against the platform itself — offline-first sync engines, background execution that survives OS policy, render paths profiled to the millisecond.
From architecture review to App Store and Play Store submission, one team owns the binary — including the privacy manifests, entitlements and review guidelines that decide whether you ship this week or next quarter.
- Swift / SwiftUI
- UIKit
- Kotlin
- Jetpack Compose
- Store compliance
APIS, STORAGE & DATABASES
The data layer is the product.
Every feature your roadmap promises is a query somebody has to serve in under 100 milliseconds. We design REST and GraphQL contracts that stay stable across versions, idempotent by default, instrumented to p99 — backed by relational and NoSQL stores tuned for mobile synchronization patterns.
Schema migrations without downtime, conflict-free offline writes, connection behavior engineered for serverless burst — the invisible work that decides whether scale is an event or a non-event.
{ "p99_latency": "84ms",
"sync": "delta · offline-first",
"migrations": "zero-downtime",
"contracts": "versioned · idempotent" }INFRASTRUCTURE CORE
Compute that bills by the millisecond, not the month.
Always-on instances burn budget while they idle and buckle when traffic spikes. We rebuild backends on decoupled serverless architecture — storage and compute separated, so idle costs nothing and load is absorbed by design: sub-second elastic activation, automatic scale-down, no connection pools held together with band-aids.
MODULE 05.2 — DATA
Storage & databases
Relational, NoSQL and vector stores — selected per workload, tuned for low-latency mobile sync.
MODULE 05.3 — DELIVERY
Mobile CI/CD
Signed, tested, reproducible releases into both app stores — on every merge, not every quarter.
MODULE 05.4 — MODERNIZATION
Legacy migration without downtime
Strangler-pattern migrations move monoliths onto elastic infrastructure release by release — revenue keeps flowing while the architecture changes underneath it.
AI SYSTEM HARDENING
Anyone can deploy a model. We lock the doors behind it.
An LLM in production is an attack surface with a personality. We treat the full pipeline — training data, model weights, inference interface — as security-critical infrastructure, with controls engineered for each threat class.
THREAT 01
Data Poisoning Mitigation
Your model is only as trustworthy as its worst training sample. We gate the training pipeline with provenance verification, statistical outlier forensics and dataset attestation — corrupted or adversarial samples are quarantined before they can bias a single weight.
- Dataset provenance
- Outlier forensics
- Pipeline attestation
THREAT 02
Model Inversion & Extraction Protection
Public inference endpoints leak more than answers: query patterns can reconstruct training data and distill the model itself. We harden the interface with rate shaping, response truncation, output perturbation and query forensics that flag extraction campaigns while they are still cheap to stop.
- Rate shaping
- Output hardening
- Extraction detection
THREAT 03
Prompt Injection Defense
Untrusted input does not get to rewrite your system's instructions. We separate privilege between instruction and data channels, isolate retrieved context, and validate every inbound instruction against policy before it reaches the model — so a poisoned document cannot become a command.
- Privilege separation
- Context isolation
- Instruction firewalls
MODULE 07 — DEVSECOPS
AI-Driven Security Automation
Security that ships at the speed of your pipeline: static and dependency analysis on every commit, continuous posture scanning across the estate, and AI-assisted triage that routes findings into your SIEM with severity, blast radius and a proposed fix — hours of analyst work compressed into the merge window.
ZERO-TRUST & GOVERNANCE
Nothing is trusted. Everything is provable.
Secure Network Architecture
Perimeter security died the day your workloads left the building. We segment systems into isolated trust zones with no implicit connectivity: every link between services is authenticated, scoped, time-boxed and revoked the moment it is no longer earned. A compromised component stays a contained incident — not a company-wide breach disclosure.
- Zero-Trust microsegmentation as the default posture
- Vulnerability assessments with prioritized, costed remediation
- Architecture reviews against modular, auditable security baselines
AI Governance, Compliance & Data Privacy
When the regulator asks why your model made a decision, "it's a black box" is not an answer. We build lineage into the architecture: every record carries its origin, legal basis and transformation history, and every inference is logged with the attribution to explain it. GDPR and CCPA stop being a deck — they become a query.
▸ SELECT AN AUDIT NODE TO INSPECT THE DECISION LOG.
09 — THE UNIFIED METROPOLIS
Architect the Future.
Edge, cloud, data, and defense—integrated into a single, sovereign, high-availability ecosystem. Let’s architect your next deployment. Submit your system requirements and build parameters below.