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Debug

Diagnose first. Rewrite second.

A bounded agent investigates likely code, model, context, or data causes with targeted probes. Each terminal result says what was observed, what was compared, and what remains advisory.

The problem

You can’t share what’s actually broken.

Posting on r/PowerBI, Stack Overflow, or the Fabric Community? The first reply is always “can you share your data model?” You can’t — it has real numbers. So you screenshot. So you paraphrase. So the answer comes back generic, and you’re still stuck.

Generic AI — Copilot, ChatGPT, Claude — will happily rewrite your measure. They have no way to know your relationship is bidirectional. They’ll keep producing more wrong DAX until you give up.

  • “Can you share your data model?”
  • “Hard to tell without seeing the relationship.”
  • “Try CALCULATE…” (no it didn’t work, the model is the problem)
  • Three days later, no answer.
r/POWERBI · 3 DAYS AGO
YTD measure returns blank for current fiscal year
5 comments · latest from StarSchemaFan: “Without seeing your date table, hard to say. Is it marked as a date table?”
no resolution · OP did not reply
01 — Upload

Drop a .pbit. Get a sandbox in 90 seconds.

Power BI templates carry your schema and zero rows of data. We parse it, generate synthetic data that respects every relationship and key, and stand up a real Power BI dataset Daxie can query.

  • Schema only — no real data ever leaves your machine
  • Synthetic data respects cardinality, keys, relationships
  • Backed by a real Power BI workspace, not a simulator
parsing template
generating synthetic data
building pbix
uploading to power bi
discovering schema
READY · ~90s elapsed
02 — Diagnose

Daxie names the failure mode before she touches your measure.

Six root-cause categories keep the investigation legible. A result can remain unresolved when available evidence does not support a confident diagnosis.

  • MODEL ISSUE — cardinality, missing relationship, inactive path
  • CONTEXT ISSUE — CALCULATE override, KEEPFILTERS, ALL semantics
  • SYNTAX ISSUE — parser-level error, circular dependency, type mismatch
  • LOGIC ISSUE — runs but produces the wrong number
  • DATA ISSUE — nulls, duplicates, locale parsing
  • DAX OK — your code is fine, the surprise is elsewhere
⚠ MODEL ISSUE
Your USERELATIONSHIP isn’t activating because the active path on 'Sales'[OrderDate] → 'Date'[Date] is still in use. The measure is correct; the relationship needs to be inactive for that join.
▸ Run · Inspect filter context · Date[FiscalYear]
03 — Share

A link that anyone can open. Real data never in it.

One click and your debug session becomes a sandbox URL. Paste it in Reddit, Stack Overflow, or your team Slack. Anyone with the link can open it, see the schema, see the failing measure, see Daxie’s diagnosis — and fork it into their own workspace to keep iterating.

  • Synthetic schema, synthetic data — we enforce it at the API level
  • Indexable by Google — your problem becomes a permanent reference
  • Forkable — the helper can pick up where you left off
  • Revocable — pull the link the moment you’re done
PUBLIC SHARE LIVE
USERELATIONSHIP returning blank on fiscal calendar
https://daxsolver.com/debug/a3f4e2…
Forkable · revocable · built on synthetic data
Why not Copilot / MCP / ChatGPT?

Diagnosis needs more than a plausible rewrite.

DAX Solver records the probes and comparison evidence used in its conclusion. When the worker, execution target, or required model-edit capability is unavailable, the receipt says so instead of presenting the suggestion as verified.

COPILOT · MCP
Writes DAX
Runs on your machine, on your private model. You can’t share what it tells you. No verification harness; it’ll confidently produce wrong DAX.
CHATGPT · CLAUDE
Talks about DAX
Pattern-matches from training data. Can’t actually run your measure to confirm a fix works. No model awareness at all.
DAX SOLVER · DEBUG
Diagnoses, then shows you proof
Investigates DAX, model, context, and data hypotheses. A receipt distinguishes sandbox verification, query comparison, advisory structural fixes, and unresolved runs.
FAQ

Common questions.

My real data stays private, right?
Yes — this is enforced at three levels. .pbit files carry schema only, never rows. We refuse to publicly share a debug session built on a .pbix upload (model, view, and API layer all check). The synthetic data we generate respects your relationships but contains nothing of your actual numbers.
Does Daxie ever just rewrite the measure for me?
It can propose supported measure rewrites after investigation and compare candidate query results when execution is available. Relationship and other structural changes on connected read-only targets remain advisory and are labelled that way.
What about my existing .pbix files?
You can still upload and debug them privately — everything works the same way. The only thing you can’t do is make a .pbix-based session publicly shareable. Re-upload as a .pbit if you want a shareable session.
Why “diagnose first” instead of just answering?
Because most DAX failures aren’t DAX failures. They’re model failures, context failures, or data failures wearing a DAX costume. If we let the assistant skip the diagnosis step it would keep rewriting your measure when the actual problem is one bidirectional relationship away.

Got a measure that’s broken right now?

Drop the .pbit. Daxie names the failure mode in 90 seconds. The URL goes in your Slack.