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oblivioX // boot000

oblivioX

intelligent systems.

DESCEND TO ENTER

01 / SIGNAL

A prompt enters the system.

Noise becomes order. Language becomes signal.

02 / BRANCH

It thinks in branches.

Paths branch and weigh. Weak branches die.

03 / REACH

It reaches for what it doesn't hold.

Meaning clusters in vector space. Move closer — it responds.

Browser, search, database, API — capabilities light up on call.

04 / SWARM

It acts as a team.

Planner, researcher, critic, verifier — messages in flight.

05 / RETURN

Everything converges.

Signals merge. A single, considered answer.

02 — Modules · Active

05 active

// modules online — awaiting signal

MOD_01

Client Intelligence · AI Workspace

The AI operating system for financial advisers.

A proactive workspace for financial advisers — client intelligence, meeting preparation, compliance, and document understanding in one operating layer, every answer grounded in sources.

open kritifin.obliviox.in →
MOD_02

On-Device AI · Browser Extension

Rewrites rough prompts into clear ones — on your device.

A free Chrome extension: select text anywhere and a small language model refines it in place, on-device by default — WebGPU with a WASM fallback. No account, no telemetry, no backend.

open refineiq.obliviox.in →
MOD_03

Knowledge Retrieval

concept

Retrieval · Reasoning

Reads thousands of sources. Returns cited synthesis.

A long-horizon research agent that reads across thousands of sources, verifies claims adversarially, and returns cited synthesis.

MOD_04

Crawl Intelligence

concept

Crawlers · Data Pipelines

Models search intent. Surfaces ranking moves.

A crawler-fed knowledge system that models search intent and surfaces the moves that actually move rankings.

MOD_05

Agent Orchestration

concept

Agents · Orchestration

Agents plan, execute, verify — in parallel.

A deterministic orchestration layer where specialised agents plan, execute, and verify complex work in parallel.

03 — Stack · Instrument

24 keys

The stack, on one board

Twenty-four tools, one per keycap, each carrying load in the work above. Hover one to read it, or just type — the board answers to a real keyboard, and every key has its own note.

// The same board, as a list.

  • MODEL

    RAG

    Grounded answers with the sources attached. No citation, no claim.

  • MODEL

    LangChain

    The plumbing between model, retriever and tool, so none of it is bespoke.

  • MODEL

    LangGraph

    Agents as state machines. A loop you can draw is a loop you can debug.

  • MODEL

    PyTorch

    Where fine-tunes and custom heads get trained before anything is served.

  • MODEL

    TensorFlow

    Inherited models, kept running and exported where the serving stack wants them.

  • MODEL

    Qdrant

    Vectors with payload filters, so retrieval narrows before it ranks.

  • SERVICE

    Node.js

    The runtime under the API surface. Streams first, so tokens arrive as they land.

  • SERVICE

    Python

    Where the pipelines, the crawlers and the evaluation harnesses live.

  • SERVICE

    FastAPI

    Typed request in, typed response out, and the schema is the documentation.

  • SERVICE

    Express.js

    Small services that do one thing. Middleware where middleware belongs.

  • SERVICE

    Playwright

    Every claim on this site is asserted in a browser before it ships.

  • SERVICE

    scraping

    Politely, on a schedule, with the parse pinned so a layout change fails loudly.

  • DATA

    PostgreSQL

    One database until it genuinely is not enough. pgvector counts.

  • DATA

    MongoDB

    For documents that were never rows — crawls, transcripts, raw tool output.

  • DATA

    Redis

    Cache, rate limit and session state. The cheapest answer is the one already computed.

  • DATA

    RabbitMQ

    Slow work leaves the request path. Retries and dead letters are the design, not the patch.

  • DATA

    n8n

    The glue nobody should write twice — webhooks, schedules, handoffs between services.

  • DATA

    Grafana

    Latency, spend and failure rate on one wall. An unmeasured pipeline is a rumour.

  • PLATFORM

    Docker

    The same image on a laptop and in production, or it does not count as tested.

  • PLATFORM

    Kubernetes

    Once there are enough services that restarting them by hand is a job.

  • PLATFORM

    AWS

    Queues, object storage and GPU when the batch is larger than the budget for idle.

  • PLATFORM

    Azure

    Where the enterprise tenancy already is, model endpoints included.

  • PLATFORM

    Google Cloud

    Run, Pub/Sub and BigQuery, for the pipelines that were already reading from it.

  • PLATFORM

    Jenkins

    The pipeline that refuses the merge. Boring on purpose, and never skipped.