Alexander Trakhimenok

Engineer · Ecosystem thinker ·Kitesurfer

Building user-owned software ecosystems.

I'm Alexander Trakhimenok. I build flagship data platform DataTug, Sneat, and the surrounding ecosystem: consumer apps, structured knowledge, open data infrastructure, and developer tools.

The common thread is ecosystem engineering — designing products, data, teams, and standards so each makes the others stronger. Not a portfolio of apps: one graph, expressed through many focused products.

Flagship: DataTug ↓Explore the ecosystemRead the story
SNEATplatformTHE SHARED GRAPHconcepts & principlesUSER-OWNED DATAconcepts & principlesOPENVAULTDBdata foundationsINGITDBdata foundationsSPECSCOREspecs & standardsGRAPHSPECspecs & standardsTRAKHIMENOK.COMconcepts & principles

Fig. 1 — The ecosystem

Projecttrakhimenok.com
Drawn byAlexander Trakhimenok
Rev2026-10-21
Scale1 : 1
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Flagship Product · Cross-Source Data Platform

DataTug: Any data. Your questions. Real answers.

FlagshipBuilding

DataTug is my flagship product: a cross-source data exploration and analysis platform that lets you connect to any data, join disparate sources in seconds, and query with visual tools, TugQL, and verifiable AI assistance. Built for engineers, data teams, and autonomous coding agents.

DataTug tugboat illustration
“Pull more from your data”Engineered to walk relationships across scattered systems
Works today across sources
SQLiteSQL ServerFirestoreinGitDBREST APIsCSV & JSON

One platform, four ways in

  • DataTug.appAvailable

    The web app: explore schemas, run queries, and chat with AI in the browser.

  • Terminal app (TUI)Available

    Keyboard-driven terminal interface (run datatug) for high-velocity local work.

  • AI Agent SkillsAvailable

    Tooling and skills for coding agents (Claude Code, Antigravity) to explore data.

  • MCP Interactive ViewsPlanned

    Interactive visual data widgets rendered directly inside your agent's chat.

Try DataTug free Documentation DataTug in Graph GitHub
Core Capabilities

From raw sources to clear decisions

Connect

Databases (SQLite, SQL Server, Firestore, inGitDB), HTTP / REST APIs, and local files.

Explore

Browse schemas, inspect data, and discover entity relationships automatically.

Query

Visual query builder or TugQL to filter, join, and aggregate across heterogeneous sources.

Analyse

Summary tables, interactive charts, and automated outlier detection.

AI Chat

Ask questions in plain language and receive verifiable answers backed by grounded query evidence.

Share & Version

Git-backed projects for queries, boards, and team knowledge with peer review.

Fig. 2 — DataTug Ecosystem Convergence

DataTug does not live in a vacuum. It is the flagship product where my broader ecosystem of open standards, storage engines, specification frameworks, and query abstractions converges into one unified user experience:

SpecScoreStandard
Specification quality & contracts

Enforces structured, AI-readable specifications, testable API contracts, and schema quality across DataTug connectors and drivers.

Read node details →
ModelSpecStandard
Universal schema standard

Defines application data models once (entities, properties, enums in compact HCL/YAML) for vendor-neutral cross-engine mapping.

Read node details →
MeaningGraphSpecification
Shared semantic layer

Maps real-world entities, ontologies, and relationships across disparate databases so humans and AI agents reason by domain concepts.

Read node details →
OpenVaultDBProduct
User-owned storage vault

Provides client-side encrypted, user-owned storage for credentials, private workspaces, and query histories.

Read node details →
DALgoStandard
Database abstraction layer

The unified multi-database query and storage engine powering DataTug's native drivers across SQL, NoSQL, and API stores.

Read node details →
inGitDBProduct
Git-backed database engine

Stores DataTug projects, query definitions, dashboards, and schema metadata as versioned files in Git with PR review.

Read node details →
TugQL (DTQL)Language
Cross-source query language

Portable declarative query syntax that joins data across disparate databases in a single, coherent query.

Read node details →

🧩 One idea, many products

Many focused products. One shared graph. Converging into a larger ecosystem. The architecture itself is the story:

  1. Composable apps need shared data.
  2. Shared data is only trustworthy if it is user-owned.
  3. User-owned data needs a vault — that's OpenVaultDB.
  4. A shared graph needs a vocabulary — that's GraphSpec inside SpecScore.
  5. Cross-system data needs exploration & joining — that's DataTug.
  6. Graph-native knowledge needs graph-native navigation — which is this website.
SneatBuildingMany niche apps on one shared graph of people, spaces, events, assets, and money — converging into the super-neat-app.OpenVaultDBPrototypeA user-owned database server with pluggable storage engines — your data, your vault, any app.SpecScoreLiveAn open standard for AI-readable software specifications — features, ideas, plans, and tasks as structured Markdown.DataTugBuildingFlagship cross-database exploration platform — explore, connect, and analyse data across disparate sources with TugQL, visual builders, and AI assistance.

🚪 Where do you fit?

Same graph, different journeys. Pick yours:

InvestFor smart-money investors who understand platforms, infrastructure, and compounding ecosystems.MentorFor experienced operators who can help sharpen fundraising, go-to-market, hiring, and focus.BuildFor exceptional engineers and product builders who want to create durable software systems.CollaborateFor founders, companies, and partners who see alignment with Sneat, OpenVaultDB, or SpecScore.Work / advisoryFocused on Sneat — open to exceptional roles or advisory where ecosystem-level judgement matters.