Ask Ava A.I.
Private, verifiable legal AI.
Law firms and AI don't mix by default.
Every firm has felt the pull of AI, and every firm has two good reasons to resist it. The usual response is to avoid AI entirely, which forfeits the productivity. Ask Ava is the other response.
Confidentiality
General AI tools are cloud services. Pasting client material into a chatbot means privileged documents leaving the building, landing on someone else's servers, under someone else's retention policy. For most firms that's a hard no, and it should be.
Hallucination
Language models answer from memory, and their memory invents authority. Courts across the country have sanctioned attorneys for filing briefs built on AI-fabricated citations. An assistant that is confidently wrong about the law is worse than no assistant at all.
It starts with defining the data.
Before a line of the application was written, the data was defined. Ask Ava runs on two kinds of data, and the distinction is the heart of the blueprint.
The firm's own record
A litigation file is a folder tree of PDFs, scans, Word documents, spreadsheets, emails, photos, and phone recordings. Ask Ava ingests all of it, on the machine:
- Scanned documents OCR'd locally into clean text
- Audio and video recordings transcribed locally
- Emails and their attachments converted and ingested alongside
- Every document cataloged into a register: name, folder, date, type
The public record, through APIs
The law itself is public data reachable through defined pipelines. Ask Ava's research desk pulls, live and on demand, from official sources:
- CourtListener (Free Law Project): Millions of published court opinions, searched Florida-first, read in full text
- RECAP archive: Federal dockets and actual filings from PACER, where motion practice lives
- flsenate.gov: The official Florida Statutes and the Florida Constitution
- flrules.org: Florida Administrative Code rule text
- myfloridalegal.com: Attorney General advisory opinions
- floridabar.org: Bar ethics opinions
- doah.state.fl.us: Administrative orders back to 1975
Scan data defines what the firm knows. Pipeline data defines what the law says. Once both are defined, the AI can be confined to them, and that confinement is what makes the whole system trustworthy.
A secure desktop environment. Not a website, not a cloud service.
Ask Ava is a native desktop application installed on a machine at the firm. "Secure environment" here isn't a policy promise. It's an architecture where the private data physically has no route out.
The AI runs locally
An on-device language model and embedding engine answer matter questions on the firm's own hardware. No document, no question about a client, and no answer ever leaves the machine.
Matters are walled off from each other
Each case gets its own workspace and its own private index. What Ava reads in one matter never informs another.
Exactly one surface goes online, and it's labeled
The legal research screen transmits only the typed research question and retrieves only public court opinions and government texts. Case documents are never part of that traffic.
Keys and logs stay local
API credentials live in a local settings file. Error and performance logs never leave the machine. An offline lockdown screen reads the engine's actual settings so the firm can verify the posture, not take it on faith.
What Ask Ava does day to day.
Ask the case file anything
Open a matter and ask the way you'd ask a colleague: “Did we file a Request for Copies?” “What does the January 7 notice say?” Every answer cites the documents it came from, one click from the original. And the most dangerous questions in litigation, the “did this happen” questions, are answered by deterministic lookup against the record, not by a model's impression. When the record doesn't contain an answer, Ava says so instead of guessing.
Research the law, with receipts
Questions are expanded into multiple searches, run Florida-first, with full opinion text read, not summaries. Every case is screened against the citation graph for negative treatment. Then an adversarial panel of researchers from two different AI companies drafts memos separately, cross-examines each other like opposing counsel, and a third model writes the final consensus memo. No model may cite anything that wasn't retrieved, so a fabricated citation is structurally impossible.
Or just talk to it
A live voice conversation, hands-free, can consult the case file inside a matter or run quick grounded legal research, with live captions and one-command saving of cases. Every research session persists, and every memo exports to a real Word document with its numbered authority table.
It tells you where its edges are.
In live testing, when the retrieved record did not answer the question asked, the memo said so rather than inventing an answer. That refusal is the trust property the entire design exists to produce. A marketing page that claims an AI is always right shouldn't be believed. This one is built to make checking easy, and that's a stronger claim.
What it delivered for Barnes Walker.
The whole file becomes askable
Thousands of pages of pleadings, discovery, correspondence, scans, and recordings become a private index that answers in seconds with citations, instead of an afternoon of manual digging.
Research that starts finished
A question that would begin with keyword roulette on a legal database returns as a drafted, cited, cross-examined memo over the actual Florida record, typically in a few minutes.
Work product that compounds
Research sessions persist, memos export to Word, and retrieved authorities file into matters where future questions can cite them. Nothing evaporates when a window closes.
Confidentiality by architecture
The firm didn't have to trust a vendor's privacy policy. Privileged material stays on the machine because the system provides no path for it to leave.
Open-record economics
The research desk runs on the public record and open infrastructure, with metered AI calls measured in cents per question, not per-seat research subscriptions.
Barnes Walker is the test case, not the ceiling.
The same blueprint fits any organization whose data is sensitive and whose answers must be right.
This is repeatable.
Law firms are the sharpest version of the problem because privilege raises the stakes, but the same pattern fits title and closing files, medical records, financial records, contract repositories, and regulatory archives.
Define the data
Scanned paper, folder trees, email archives, recordings, databases, or external APIs. If it can be pointed at, it can be defined; if it can be defined, it can be indexed.
Build the secure environment around it
A desktop application on your hardware, with local AI for the private data and narrow, labeled pipelines for the public data. Your material never leaves your building.
Confine the AI to the defined record
Models read what retrieval supplies and cite what they read. Deterministic questions get deterministic answers. The system says “not in the record” instead of guessing.
Make verification one click
Every claim traces to a source a human can open. The product's job isn't to be trusted blindly. It's to make checking effortless.
If your data can be defined, this environment can be built around it.