Deep Tech & Enterprise Engineering

Complex Systems.
Not just Prompts.

We build "Intelligent Systems" where AI is just the tip of the iceberg. Beneath the surface: fault-tolerant architecture, legacy integrations, and strict business logic.

Why GPT Wrappers Fail in Enterprise

Business needs processes, not chatbots. We bridge the gap between "Magic AI Demo" and "Production Reality".

01

Legacy Data

Your data isn't in a Vector DB. It's in Oracle (2010), SAP, or 1C. We build the adapters to fetch it.

02

Security & PII

You can't send customer names to OpenAI. We deploy On-premise LLMs inside your perimeter.

03

Strict Logic

Neural networks hallucinate. We wrap them in code constraints (Guardrails) to ensure reliability.

Case #1 FinTech / High-Load

Sber Analytics Middleware

Client: Sberbank Largest Bank in CEE 106M+ Clients

Challenge: Deliver real-time data to AI risk models without crashing the monolithic banking core under 15k EPS load.
Solution: Fault-tolerant Data Bus (CDC + Kafka) with complete core isolation.

15k
EPS
<1s
Latency
Source Zone
Core BankingORACLE
Monolithic System
Redo Logs
Integration Layer
CDC Connector
Debezium
Raw Events
Kafka Topic
Stream Processor
Masking • Validation • Deduplication
FlinkRedis
Clean Events
Public Topic
DLQ
Error Handling
Analytics Zone
Enterprise DWH
Greenplum
Data Lake
S3 MinIO
ML Feature Store
Redis
Case #2 CV / Internal Tools

Design Copilot

Client: Avito World's #1 Classified 60M MAU

Challenge: Automate Design QA across 150+ designers.
Solution: A hybrid engine (Computer Vision + Code AST) that checks Figma layouts against the Design System in real-time.

View Product Page
2x
Faster TTM
-30%
UI Bugs
Figma Selection

Layer ID: 124:4
Frame: "Cart_V2"

Sync Analysis Engine
Visual StreamCV / CNN
  • Padding (px)
  • Visual Noise
Code StreamAST / JSON
  • Parse Tree
  • Token Map
Comparator & RulerConflict Resolution

If (Visual != Token) -> Error

Result: Native Comment
+
Design CopilotNow
Blocker Issue
Spacing violation detected.
Current: 21px (Custom)
Required: 24px ($spacing-3xl)

How we engage without SOW?

Complex systems cannot be estimated "at a glance". We use a phased approach to reduce uncertainty. You pay for the result of each stage, avoiding the "black box" trap.

01

Discovery & Audit

2-3 weeks. We study legacy code, interview stakeholders, and draft the Architecture Vision. Output: Roadmap & Risk Assessment.

02

PoC (Proof of Concept)

4-6 weeks. We build the "skeleton" on real data. Testing hypotheses (e.g., RAG quality). Output: Working Prototype.

03

Production Engineering

3-6 months. Kubernetes, CI/CD, Tests, Monitoring. Output: Production System.

Internal Project

Automated Content Factory

Example of internal process automation: GenAI Pipeline from trend watching to video publishing.

01. Ingestion
Trend WatcherPYTHON

Monitoring Telegram & Trends. Topic Clustering.

CeleryRedis
AI ScreenwriterLLM

Script generation (Hook-Body-CTA). Timecodes.

GPT-4o
02. Smart Asset Factory
Central Asset Management VECTOR DB
Stock Library
Video .mp4
Memes .gif
Gen-AI Pipeline
Midjourney
ElevenLabs
Infrastructure

COMPUTE CLUSTER

High-Load Environment
03. Assembly & Control
Auto-EditorFFMPEG

Composition on timeline.

Admin UI

Human Approval Loop.

Publisher API
YouTube
TikTok
Insta

Enterprise Standards

IP Rights & NDA

We work under strict NDA. All IP rights for code and architecture are transferred to the client. No Vendor Lock-in.

Learn More →

Security (On-Premise)

Local LLM deployment. Data sanitization gateways. Your data never leaves your perimeter.

Scalability

Kubernetes-ready microservices. CI/CD pipelines. We build systems designed to grow.

Ready for a "Big" Project?

Book a free 30-min architectural review. We will understand the task, assess risks, and draft a high-level Roadmap.

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