Cited research, audit-ready memos, footnotes modeled on peer filings, and schedules that foot to the penny: what the category should do, how GAAP IQ does it, and a checklist to test any vendor against, including us.
AI technical accounting software applies AI models to the judgment side of accounting: researching how US GAAP applies to a transaction, documenting the conclusion in a memo, drafting the footnote disclosure, building the supporting schedule, and codifying the policy. It sits upstream of close automation, which reconciles numbers that already exist, and apart from general chatbots, which answer from open web training data. The defining property is verifiability: answers grounded in authoritative and interpretive guidance, with citations a reviewer can open and check at the page level.
GAAP IQ is built to that definition: seven tools that carry a hard question from cited research to the memo, the footnote, the schedule, and the policy, with one rule underneath: answers arrive cited, and every citation is checked against its source before you see it. The rest of this page covers what the category should do, how the product classes differ, and how to test any vendor before you pay one.
What does the guidance say, and can you prove it: that is the job everywhere. What changes is the desk it lands on, and what has to exist by Friday.
Seven capabilities define the category. Each one maps to a GAAP IQ tool you can open and test today, and each has a failure mode worth knowing before you buy anything.
An uncited answer is a liability in this domain: you cannot take it to a partner, an auditor, or the file. The software should ground every claim in authoritative and interpretive guidance and let a reviewer open the source at the page, not just name a document.
An orchestrator plans the research and fans parallel researchers out across 27 indexed Big 4 handbooks plus FASB and SEC sources. Every claim carries a pill that opens the handbook at the exact page with the supporting text highlighted. A second model strips any citation it cannot support before you see the answer, and when the Big 4 read a judgment area differently, the positions appear side by side.
Explore ResearchIQPositions get stronger when you can show how comparable companies handled the same question. The software should search real filings rather than summaries of them, and pull exact reported figures rather than reading numbers out of prose.
FilingsIQ searches SEC EDGAR full text across filings since 2001, builds peer cohorts by SIC industry code, extracts footnotes at inline-XBRL boundaries, and pulls reported figures straight from XBRL data. Every answer cites numbered references that link back to the specific filing on EDGAR.
Explore FilingsIQThe memo is the deliverable an auditor reads, so drafting help has to be reviewable: what the AI concluded, what it assumed, and what it changed. Silent rewrites disqualify a tool for documentation work.
MemoIQ works from a plain-words description or the agreement itself: it scopes the issues, drafts issue by issue with cited analysis, and pauses for judgment calls, or runs on autopilot and flags each assumption in the margin. AI review arrives as tracked changes with Accept and Reject, and the auditor's returned Word comments can be imported and answered in a response copy with your edits as redlines.
Explore MemoIQA footnote has two masters: the disclosure requirements and the conventions readers expect. The software should check coverage against the requirements and show how comparable companies actually word the disclosure.
DisclosureIQ starts with a short multiple-choice questionnaire, pulls how up to three comparable public companies disclose the topic in their latest 10-Ks at exact footnote boundaries, and drafts your footnote with citations to the handbook guidance. Every draft ships with a requirement-by-requirement checklist: met, needs a detail from you, or not applicable with a one-line reason.
Explore DisclosureIQA policy manual that restates the standard helps no one. The software should pin down the entity's elections, thresholds, and methods, and keep the manual versioned as positions evolve.
PolicyIQ pins your elections down by questionnaire and drafts a policy, not a summary: elections made, thresholds set, methods chosen, who does what and when, with page-level handbook citations after each position. Approvals build a versioned, exportable manual, and a plain-words change applies in place.
Explore PolicyIQLanguage models are the wrong tool for arithmetic that has to tie out. The software should use AI to read the arrangement and deterministic code to compute every number.
In ScheduleIQ, the AI only extracts inputs and surfaces every assumption for you to confirm; deterministic engines compute lease amortization, debt effective-interest walks, and SBC rollforwards. A final-period rounding plug lands balances at exactly zero, or par, so an auditor recomputing any row gets the same cents. Output is an Excel-ready workbook with a cited basis note.
Explore ScheduleIQnewTechnical questions rarely stay inside GAAP. The software should point the same cited, verified research method at federal tax law rather than bolting on a second, looser tool.
TaxIQ runs the same orchestrated research engine over the Internal Revenue Code and Treasury Regulations. Conclusions cite the exact IRC section and Treasury Regulation with the source text one click away, and when a rule changed recently, the answer states the effective date and which tax years each version governs. The corpus grows through the beta.
Explore TaxIQbetaThree other product classes get shortlisted against this category. The table tests the properties that matter for technical accounting work. Columns are categories, not vendors, because vendors change faster than categories do.
| What to check | GAAP IQ | General AI chatbots | Close automation platforms | Demo-gated technical accounting tools |
|---|---|---|---|---|
| Page-level Big 4 citations | Every claim opens the handbook at the exact page, supporting text highlighted | No licensed corpus: answers draw on open web training data | Built to tie out numbers, not to cite interpretive guidance | Varies: confirm page-level depth in the demo |
| Citation verification before display | A second model checks every citation against source text and strips what it cannot support | Citations, where offered, are not checked against the source | Not a research product, so no citation layer to verify | Rarely described publicly: ask how bad citations are caught |
| Transparent public pricing | $0, $149, and $399 per month, published in full | Published, but for a general assistant, not this work | Typically quote-based | Typically quote-based, behind a demo |
| Self-serve free start | One-time free trial, no credit card required | Yes | Usually demo-first | Demo required |
| Deterministic schedule math | Engines compute every number and the AI only extracts inputs: workbooks foot to the penny | Figures are model-generated | Often yes, inside their own subledgers | Varies: ask who computes the numbers |
| EDGAR benchmarking | Full-text search of filings since 2001, peer cohorts, figures pulled from XBRL data | Web search without exact footnote extraction | Generally not offered | Varies by tool |
| Footnote peer modeling | Drafts modeled on up to 3 peer 10-Ks at exact footnote boundaries | Not offered | Generally not offered | Varies by tool |
Category columns describe how each product class typically works as of August 2026, based on public product pages. Individual vendors vary: run the evaluation checklist below on every shortlisted tool, including ours.
Every product class here is credible at its own job, and this table is not a claim that GAAP IQ replaces them at theirs. It is a claim about this work: page-level citations into Big 4 handbooks, verification before display, and pricing you can act on without a sales call.
Eight tests you can run in any vendor's demo, ours included. They take under an hour, and they separate mechanism from marketing.
Pick one sentence of an answer and ask where it comes from. A real citation opens the source at the page with the supporting text visible. A document name without a page is a bibliography, not a citation.
The failure mode of AI research is the confident wrong cite. The right answer is verification before display: a second check of every cited claim against the source text, with unsupported citations stripped rather than shown.
For any schedule output, ask whether figures come from the model or from code, then recompute one row yourself. Deterministic engines return the same cents every time; models do not.
Pick a judgment area where the Big 4 read the guidance differently and see whether the tool surfaces the positions side by side or averages them into false confidence.
Ask the tool to revise a paragraph of your draft. Edits should arrive as tracked changes you accept or reject, never as silent rewrites of your document.
Public pricing and a self-serve start mean the vendor expects the product to sell itself in use. Quote-based pricing behind a mandatory demo moves that risk to you.
Content should never train models, AI requests should carry zero-data-retention terms, and uploads should delete on a clock. Ask for the published version of each claim, not a verbal assurance.
Review happens in Word and Excel, not in an app. Exports should carry numbered references with quoted sources so the work stands on its own in front of an auditor.
Our own answers to the data questions are published on the trust page. And the fastest evaluation is a question you already know the answer to: our guides work through sales commissions under ASC 340-40, profits interest units in a business combination, and the ASC 606 five steps applied to advisory fees at the depth a cited answer should reach. More worked material lives in guides and resources.
Every plan includes all seven tools at full quality (TaxIQ in beta). Follow-ups, tables, and pushback all live inside one research session, and on paid plans, memos, disclosures, policies, and schedules never count.
One-time trial
One full research session, cited and verified, plus one memo, one disclosure, one policy, and two schedules. Word and Excel export.
or $1,490/yr (two months free)
20 research sessions a month, follow-ups never count. Unlimited memos, disclosures, policies, and schedules, with autopilot memo builds and AI review.
or $3,990/yr (two months free)
Unlimited research sessions, everything in Professional, and priority support. For heavy caseloads and firms.
No credit card required to start. Cancel anytime in Settings. All purchases are final. Rolling out to a team: contact us.
One cited research session and a draft in every tool, free, before any vendor gets your budget.
No credit card required
AI technical accounting software applies AI models to the judgment side of accounting: researching how US GAAP applies to a transaction, documenting the conclusion in a memo, drafting the footnote disclosure, building the supporting schedule, and codifying the policy. It sits upstream of close automation, which reconciles numbers that already exist, and apart from general chatbots, which answer from open web training data. The defining property is verifiability: answers grounded in authoritative and interpretive guidance, with citations a reviewer can open and check at the page level.
Close automation reconciles and ties out numbers that already exist: reconciliations, flux analyses, subledger postings. AI technical accounting software works upstream of those numbers, on questions where the answer is a judgment supported by guidance: how to treat the transaction, what the memo should say, what the footnote must disclose. Many teams run both, because they answer different questions.
A general chatbot answers from open web training data and cannot open a licensed source to back a claim. GAAP IQ retrieves from 27 indexed Big 4 interpretive handbooks plus FASB and SEC sources, cites every claim to the exact page with the supporting text highlighted, and runs a verification pass that strips any citation it cannot support before the answer is displayed.
Before an answer is shown, a second model checks each cited claim against the text of its source and strips citations it cannot support. What survives is a claim whose citation opens the handbook at the exact page with the supporting text highlighted, so a reviewer can confirm it in seconds.
The corpus indexes 27 Big 4 interpretive handbooks (KPMG, EY, PwC, and Deloitte) with 33K+ searchable guidance passages across 23 ASC topics, alongside FASB and SEC sources. FilingsIQ searches SEC EDGAR full text across filings since 2001. For federal tax, TaxIQ (beta) searches the Internal Revenue Code and Treasury Regulations.
GAAP IQ publishes pricing: the Free plan is $0, a one-time trial with one full cited research session plus one memo, one disclosure, one policy, and two schedules. Professional is $149 per month, or $1,490 per year (two months free), with 20 research sessions each month and unlimited memos, disclosures, policies, and schedules. Enterprise is $399 per month, or $3,990 per year (two months free), with unlimited research sessions and priority support. Many tools in the category quote pricing only after a demo.
Yes. The Free plan is a one-time trial: one full research session, cited and verified, plus one memo, one disclosure, one policy, and two schedules, with Word and Excel export. No credit card is required to start, paid plans can be canceled anytime in Settings, and all purchases are final.
No, and a vendor that suggests otherwise should worry you. GAAP IQ's output is a research starting point, not professional advice: every conclusion carries clickable citations so a qualified professional can verify it, and exports include numbered references with quoted sources so the work can be checked outside the app.
No. Customer content is never used to train AI models. Requests are routed to model providers under zero-data-retention arrangements, work is segregated per account and encrypted, and uploaded documents self-delete within 24 hours.
Yes. The corpus spans 23 ASC topics, including revenue recognition under ASC 606 and leases under ASC 842, drawn from Big 4 interpretive handbooks with 33K+ searchable guidance passages, and it keeps growing.
MemoIQ drafts issue by issue with cited analysis and exports to Word with numbered references. Whether an auditor accepts a memo depends on the judgments and the facts, which stay yours: the tool pauses for judgment calls or flags each autopilot assumption in the margin, AI edits arrive as tracked changes with Accept and Reject, and the auditor's returned comments can be imported and answered in redlines.
In ScheduleIQ, the AI never computes numbers: it extracts inputs and surfaces every assumption for confirmation, and deterministic engines compute each row on rounded balances so the workbook foots exactly as displayed. A final-period rounding plug lands balances at exactly zero, or par, and an auditor recomputing any row gets the same cents. A cited basis note explains the methodology.
More answers, including billing and data handling detail, live on the full FAQ. For how the product is built and what we refuse to claim, see about GAAP IQ.