Ask questions about patient-adjacent data
without a row of PHI ever reaching an AI model.
Patient-adjacent data, HIPAA and HITECH exposure, and the highest breach cost of any industry. Your team can't run PHI through a general AI tool and hope no one notices. Edilitics gives you governed AI analytics with an audit trail - not a promise, an architecture.
average cost of a healthcare data breach - the highest of any industry, 15 years running
In 2025, IBM's Cost of a Data Breach Report found healthcare breaches average $7.42 million each, with the highest per-record cost of any sector at $185 - and take 279 days to even detect. As of January 2026, HHS's Office for Civil Rights can levy HIPAA penalties up to $2,190,294 per violation category under its willful-neglect tier, and has already settled more than 50 cases under its active risk-analysis enforcement initiative. Every one of those numbers gets worse the moment PHI-adjacent data leaves your environment in a prompt nobody logged. You need the zero-raw-data architecture and an audit trail to go with it - not a policy that says it won't happen.
What Actually Happens
A question about patient-adjacent data comes in.
Here's where the real data actually goes.
Same question. Two different ways it plays out.
Today
“Why did the denial rate spike for this client hospital?”
- Someone needs a fast answer - a report is due today
- Fastest path: paste patient-adjacent fields into a general AI tool
- No log of what was pasted, or where it went
- Nobody finds out until a breach review asks the question first
With Edilitics
Same question, asked in AskEdi instead
- No real row ever leaves the database, in any privacy mode
- Answer comes back in plain English, just as fast
- Every query logged - what ran, and what the AI generated
- Nothing to explain after the fact, because nothing left
One Platform, One Governance Boundary
Patient-adjacent data: connect, clean, report, ask -
it never leaves the platform to do it.
The same path every question takes, end to end - each step shown below.
One audit trail, every hop
Connect
Profiled, not stored raw
Schema, DQ, and AI-readiness scored the moment your warehouse or database connects - raw rows are never stored.
Clean
No standing unmasked export
Zero-trust pipeline previews run AES-encrypted, purging in 30 minutes - no spreadsheet sitting around with unmasked rows.
Report
No re-export cycle
The dashboard stays current on its own - nobody re-exports patient-adjacent data into a deck every reporting cycle.
Ask
Governed by privacy mode
AskEdi reasons on the governed metadata layer only. The query that ran is always visible next to what the AI generated.
Connect your EHR-adjacent warehouse or claims database, clean and join sensitive tables in Transform, keep the compliance dashboard current in Visualize, and take the live follow-up in AskEdi - under whichever privacy mode your compliance posture calls for.
Three Privacy Modes, Zero Raw Rows
You choose what the AI sees.
It never sees a raw PHI-adjacent row.
Every mode blocks raw data transmission - the difference is how much metadata context the AI gets to reason with.
Private Mode
Column names are replaced with anonymous identifiers before the AI ever sees them - it reasons on structure only, never real schema.
Balanced Mode
Real column names and DQ statistics are shared for context, but live row data is always blocked - the default for most regulated teams.
Full Context Mode
Adds aggregated top-frequency values and prior analysis context - still never a single raw row, even at maximum intelligence.
Not Just Confident-Sounding
An answer you can check,
not just trust.
In patient-adjacent data, a fast answer only matters if the number behind it actually holds up.
Analysis View on every answer
The exact query that ran against your database, one click away - not a black box you have to trust.
Methodology Notes, in plain language
Sample size, method, and test result stated for every forecast or root-cause read - generated by Edilitics, not the AI.
Zero raw rows sent to any LLM
Architecturally enforced, not prompt-engineered - the AI reasons on schema and stats, never your actual data.
No charge on a bad answer
Failed, empty, or malformed results are never billed - the system doesn't paper over its own failures.
Ask Directly
Questions healthcare tech teams actually ask AskEdi
Ask any of these directly, without a new tool or a compliance review for each one.
“Why did claim denial rate spike for this payer last quarter?”
“What if we shift 10% of intake volume to our fastest-processing client - impact on turnaround time?”
“Forecast claims volume across our client base for the next two quarters.”
“Which client hospital shows the highest concentration of data quality issues?”
“Where should we focus support to reduce denial rates across our client base next quarter?”
“Summarise this quarter's client performance dashboard the way I'd report it to the board.”
Not sure this is your situation? See all six solutions.
Everything you need to know before you decide.
No sales call needed. If you have a question we haven't answered here, reach out directly.