Enqualia

Enqualia

From behind to
frontrunner.

Custom AI, built and run for you: your data gets a shape, your questions get your answer.

Schedule a demo
Scroll, and watch it work

01 · Voice

The assistant you simply talk to.

Say what the business needs and Qualia takes it from there. It manages your workspace, prepares what is missing and makes what is useful: the table, the model, the report, the reply. Longer work goes to its workers while you keep talking.

  • Talkask out loud, hear it answer
  • Manageprepare and make the work
  • Anywhereon the web and on your phone

In the graphListening. A wave rolls through its rings while it listens, and it swells with its own voice when it answers.

02 · Ingest

Point it at a file, a URL or a question.

CSV and JSON parse deterministically. PDFs and web pages are structured against the schema the table already has. Every record keeps where it came from, and a dry run shows exactly what would change before anything is written.

  • CSV · JSONparsed exactly
  • PDF · webfit to your schema
  • Dry runbefore any write

In the graphIngesting. Records pour into a table. This is the shape Qualia takes whenever it reads something in.

03 · The fit

It builds its own model of your data.

Every column is classified from its own values, every record gets a position, and records that are alike end up near each other. Every number becomes a prediction target, learned from the rest of its row. No schema to define, no model to configure, no training run to wait for.

  • 8rows is enough
  • 16dimensions at most
  • 0GPUs, all numpy

In the graphBuilding its model. Rows lift off the table and settle into rooms, one colour for every zone of similar records.

04 · Predictions

Records that are alike predict each other.

Every record gets a position learned from all of its fields, its free text included, so records that behave alike end up side by side in the same semantic zone. That position is what predicts: ask for a missing number and Qualia reads it from where the record sits, with a range, scored on rows it has never seen.

  • All fieldsfree text included
  • A rangewith every number
  • Unseen rowswhere it is scored

And when a plain average would do better, you get that average, labelled.

In the graphPredicting from similarity. Qualia becomes the zone itself: records sit by similarity, and a new one is read from where it lands.

05 · Questions

Ask anything about your data. It works through all of it

A question becomes a precise program that counts, filters, ranks, compares and predicts across every record, not a sample pasted into a prompt. The answer is written from what the program found and checked against it, so the numbers you read are the numbers it found.

  1. 1Understand
  2. 2Every row
  3. 3Check
  4. 4Answer

In the graphRunning a query. A table scanned row by row. Every row counts, whatever the question.

06 · Missions

Ask for a piece of work, get several specialists

A mission plans up to four workers and runs them in parallel, each a full agent with the whole workspace in context. Before a report is composed, a critic checks its load-bearing numbers against live data.

  • Report writer
  • Model trainer
  • Data exporter
  • API builder

In the graphRunning a mission. Specialists circle the centre, one light for every worker.

07 · APIs

It builds new APIs and puts them live.

Ask for an endpoint and Qualia writes it, checks it and deploys it, ready to call. The key decides what any agent may touch, and that rule is enforced in the code, not in the prompt. Connect your own agent over MCP and it gets the same tools under the same rules.

  • Liveready to call
  • MCPthe whole tool surface
  • Per callwhat it spent, in the header

In the graphBuilding an API. A cube solves itself while the endpoint is built.

08 · Watchers

Watchers keep an eye out

Tell it what matters: a table, a folder, a mailbox, or a goal in your own words. It checks every 15 minutes and stays silent unless something really changed. When it speaks, the alert lands on your phone with the next steps attached.

  • 15 minbetween checks
  • 2 to 4next steps per alert
  • Quiet hourshold the buzz, never the alert

In the graphKeeping watch. A radar sweep while a watcher looks, a clock face when the work runs on a schedule.

09 · Mail

Replies drafted, sent by you

Connect a mailbox and Qualia reads it, answers questions about it and drafts replies. It has no way to send. You read the draft and press send.

  • 0ways for it to send
  • Draftsready for your review
  • Youpress send

In the graphDrafting a reply. The draft is written, then the flap folds shut. Sending stays on your side.

The workspace graph

Everything it makes lands in one graph.

Tables, models, APIs, documents, mail and watchers hang off Qualia as hubs, with their records and pages around them. When work goes out, a messenger in the colour of the job glides along the edge to where it lands.

Tables
Models
APIs
Documents
Mail
Watchers
Qualia

The messengers wear Qualia's own colours: teal for data, magenta for models, gold for APIs, rose for documents, mint for mail, emerald for watchers.

Pricing

Fixed plans. Zero surprise invoices.

Every plan includes a monthly pool of entanglements with a live meter, like the AI tools you already use, but for your own workspace and endpoints.

Usage is measured in entanglements. Every call tells you what it spent, in the response header and in the dashboard.

Starter1 production project, 3 seats€97/month300K entanglements included monthlySee full plan
Best valueGrowthOne workspace per client, white-label€297/month1M entanglements included monthlySee full plan
ScaleUnlimited projects, SLA€897/month3M entanglements included monthlySee full plan

Every call tells you what it spent, in the response and on your dashboard.

Compare all plans

Annual billing saves two months.

See it on your data.

A 30-minute call with the founder. Bring one messy source.

Schedule a demo
Antoni Elkenbracht

Antoni Elkenbracht

Founder

MSc Artificial Intelligence, Utrecht University. The gate, the entity models and the query layer come out of the thesis work. The method is the credential, and it is written down.

LinkedIn