Multi-provider LLM access
A first-party abstraction over 40+ providers — Anthropic/Claude, OpenAI, DeepSeek, Gemini, Mistral, Groq, xAI/Grok, and local Ollama as a fallback — behind one interface with retries, circuit breakers, and health checks.


// AI-native software engineering
We build AI development systems — the models, agents, orchestration, and infrastructure that turn large language models into dependable software — together with the governance layer that keeps them honest.
// about
Vasic Digital is a focused engineering practice building an interconnected family of AI-development products and reusable modules. Rather than one monolith, the work is organized as a fleet: large product applications on top of dozens of small, independently-tested, decoupled modules — so proven parts are reused across every product instead of rebuilt.
The backbone language is Go, complemented by Kotlin & Kotlin Multiplatform, TypeScript/React, Python, Swift, and Shell — chosen per job. What ties the fleet together is discipline made mechanical: every project inherits a shared engineering Constitution as a Git submodule, and every capability a product advertises must be backed by an automated, evidence-producing test. A feature is not "done" when the tests pass; it is done when a real user can actually use it, and there is captured evidence to prove it.
// what we do
We build the substrate for AI systems — the hard part beneath the app.
A first-party abstraction over 40+ providers — Anthropic/Claude, OpenAI, DeepSeek, Gemini, Mistral, Groq, xAI/Grok, and local Ollama as a fallback — behind one interface with retries, circuit breakers, and health checks.
Headless CLI coding-agent control planes, graph-based agentic workflows, multi-round "AI debate" consensus, and DAG/pipeline runtimes.
A trust layer that scores models with a mandatory comprehension gate ("Do you see my code?") plus latency, streaming, function-calling, vision, and embeddings tests — exporting a verified-only configuration.
RAG, vector databases, embeddings, and fused agent-memory engines (Mem0 + Cognee + Letta) with infinite-context compression.
Guardrails, PII detection, adversarial red-team fixtures, and input canonicalisation — safety built into the substrate, not bolted on.
// tier 1 — flagship
Our flagship line spans the full AI-development lifecycle. In priority order.
A free-world alternative to JIRA — the flagship of the Helix-Track line.
An ensemble LLM service that lets multiple models debate and ships the answer they agree on.
A distributed AI development platform that divides work across SSH-managed workers with checkpoint/rollback.
One binary, six modes: OpenAI- and Anthropic-compatible inference from laptop to cluster, over HTTP/3.
A distributed operating system for AI compute, from datacenter GPUs to edge handhelds.
One interface, 43 providers — with circuit breakers, retries, and health baked in.
One control plane for every headless CLI coding agent.
Verify. Monitor. Optimize. The single source of truth for LLM and provider verification metadata.
One memory brain for AI agents — four best-in-class engines, fused.
// quality & governance — our differentiator
Two pillars make the whole fleet coherent and trustworthy.
A universal, project-agnostic engineering rulebook shipped as a Git submodule and inherited by every project across a 140+-repository fleet. It encodes non-negotiable discipline — anti-bluff evidence gates, false-positive immunity, data and host safety — that a project may extend but never weaken. One submodule bump upgrades the rules everywhere, and every gate is paired with a mutation test that proves the gate itself isn't a sham.
Anti-bluff QA orchestration. It runs written YAML test banks and fully-autonomous, LLM-plus-computer-vision QA sessions across Android, Android TV, Web, and Desktop — and it refuses to score a PASS without captured runtime evidence: screenshots, logcat, video, stack traces. "We tested it" becomes "here is the video, the logcat, and the ticket."
// tier 2 — utilities
Product-grade tools that stand on their own.
Advanced multi-protocol, encrypted media collection management — detect, catalog, and enrich everything you own.
Markdown in, professional video course out — AI-enhanced, multi-platform.
See the UI like a user — computer vision plus LLM vision for analysis and navigation.
Turn documentation into a verifiable feature map for QA automation.
No tracked document can fall out of sync — content-hashed, bidirectional, atomic.
Every alert reaches the right destination — no command syntax required.
Your task board and your source-of-truth, impeccably in sync — both ways.
Build once, reuse everywhere — a fleet of small, decoupled, independently-tested Go and KMP modules.
// tier 3 — heritage
Our DevOps heritage: declarative JSON turned into fully-provisioned, Dockerized servers.
Run your mail server like the boss — describe it in JSON, deploy it anywhere.
The shared engine behind every Server Factory.
QEMU VM images, managed like artifacts — download, run, network, publish.
Compress, publish, and reuse your Parallels VM images across every machine.
// technologies
// portfolio
A unified, evidence-based portfolio of the Helix family, the vasic-digital utilities, and the Server Factory toolchain.
// contact
Anyone can wire an app to an LLM. We build the part that is hard: AI systems that are verifiable, reusable, and honest. We don't ask you to trust the green checkmark — we show you the evidence behind it.
Email
i@mvasic.ru
GitHub
github.com/vasic-digital