Instead

Tax software has a specific problem that AI has mostly not touched. Most AI tax tools answer questions — they research, they explain, they summarise — and then hand you back to a thirty-year-old preparation system to actually do the work.

That leaves the tedious half exactly where it was. Research is the interesting part of tax and the smaller part; preparing, reconciling and filing is where the hours go.

Instead's claim is that it replaces the engine rather than sitting beside it, and there is one concrete fact that makes the claim credible rather than aspirational: it can file. E-filing requires IRS authorisation, which is a regulatory process rather than a feature, and it is what separates a tax platform from a tax assistant.

What Does Instead Actually Own?

• Five stages, one agent: research, planning, preparation, filing and defence — rather than research assistance bolted onto existing software.
• It can actually file: e-filing with the IRS, 48 states and cities, electronic and print, for all five entity types.
• Research across 1,500+ authoritative sources including the Internal Revenue Code, Treasury Regulations and case law.
• Multi-entity by design — 1040s link to S corps, partnerships and trusts, which is how real tax situations are actually structured.
• The platform is free with unlimited users and entities; agent work is charged per credit on annual agreements.

Why Does IRS E-File Authorisation Matter Most?

Instead states e-filing with the IRS, 48 states and cities, electronic and print filing for all five entity types, and describes itself as the first company in decades to receive IRS approval to e-file.

That authorisation is the most substantive claim on the site, and it is worth explaining why. Becoming an authorised e-file provider is not a matter of building software — it requires application, suitability checks, and passing IRS testing against real transmission requirements. It is a deliberately high barrier, which is why the roster of providers has barely changed in decades.

The practical consequence is what makes it matter. A tool that researches and prepares but cannot file leaves you re-entering the return into another system, which is where errors are introduced and where the time saving evaporates. Filing is the step that closes the loop.

Coverage across all five entity types — 1040, 1120, 1120-S, 1065 and 1041 — is the second half of the claim and equally important. A platform that files individual returns but not the partnership behind them only handles the easy half of most real clients.

This is the checkable, regulatory fact underneath the marketing, and it is the right thing to weigh most heavily.

Authorisation is the line between advice and action, and it is what separates this from research tools. TaxGPT answers tax questions; filing on someone's behalf is a regulated act.

Any tool can research a tax question. Filing requires the IRS to authorise you, which is why that roster has barely changed in decades.

Multi-Entity Linking Reflects How Tax Actually Works

Instead links 1040s, S corps, partnerships and trusts rather than treating each return as a separate job.

That structural decision matters because real tax situations are not isolated returns. A business owner's individual return depends on the K-1 from their S corporation, which depends on how the entity allocated income, which may depend on a trust holding shares.

Traditional software handles these as separate files, so a change to the entity return means someone manually carrying the revised K-1 into the individual return — and remembering to. That handoff is a reliable source of both errors and rework.

Linking them means a change propagates. It also means the planning question — what happens to the owner's total position if we change the allocation — becomes answerable rather than requiring three parallel manual recalculations.

For anyone serving business owners or high-net-worth individuals, that is the difference between a tool that helps with returns and one that helps with a client.

Research Grounded In Authority, Not Absorbed From The Web

The research capability draws on more than 1,500 authoritative sources including the Internal Revenue Code, Treasury Regulations and case law.

Sourcing is the question that decides whether AI is usable in tax at all. A general assistant has absorbed a great deal of tax material of unknown vintage and unknown provenance, and cannot tell you where an answer came from — which is fatal in a field where a threshold changed in April and a position must be defensible in a file.

Reasoning over primary authority is the right architecture, and it is what lets an answer be checked rather than trusted.

The document side complements it: extraction from K-1s, W-2s, 1099s and IRS transcripts. That is the genuinely tedious part of preparation, and unlike research it has an objectively correct answer you can verify against the source document.

The caution belongs where it always belongs in this field. Professional responsibility for a filed return sits with the preparer who signed it, and no software transfers that. Read the authority a research answer cites before relying on it, and verify extracted figures against the documents — a misread figure in a return is your error regardless of what extracted it.

Grounding in primary authority is the same discipline Blue J built its reputation on, and the reason both are more defensible than a general model asked a tax question.

• Verify extracted figures against the source document; a misread box on a 1099 becomes your error at signature.
• Read the cited authority before relying on a research answer, as you would with any source.
• Test currency by asking about a rule that changed in the last twelve months.
• Check multi-entity propagation by amending an entity return and confirming the linked 1040 updates.
• Keep your own record of what you relied on, since the file must show why a position was taken.

Free Platform, Credits For Agent Work

Instead's pricing structure is unusual and worth understanding: the platform is free with unlimited users and entities, and AI agent work is charged per credit on annual agreements.

This inverts the normal model, and mostly in the customer's favour. Traditional tax software charges per seat and per return, which penalises a growing firm for adding staff and makes every additional client a marginal cost decision.

Charging only for agent work means the software itself imposes no cap. A firm can put every member of staff on it and manage every entity without a licensing conversation, and pay only for the automated work actually performed.

The variable to model is therefore credit consumption per return rather than a seat count. That is genuinely harder to predict in advance and considerably fairer once you know it, because a simple return costs less than a complex one — which is how firms bill their own clients anyway.

The claim of 2,000 returns prepared by a single tax staff member is the figure this structure is meant to support. Treat it as a best case with no stated methodology: return complexity varies enormously, and 2,000 straightforward individual returns is a very different proposition from 2,000 with entity work behind them. Model your own credit consumption on a representative sample before committing to an annual agreement.

Credit pricing for agent work is becoming the norm wherever the agent does something billable — the same shift visible in document platforms like Ironclad and Black Ore.

Piloting It On Returns You Already Filed

Tax software can only be evaluated honestly against returns where the correct answer is already known, and the season structure means you have last year's to test with.

The bar is step three. An extraction error you did not catch is an error you would have signed.

1. Choose five returns you filed last year across at least two entity types, keeping the filed versions for comparison.
2. Upload the real source documents — K-1s, W-2s, 1099s, transcripts — and let the platform extract rather than keying anything in.
3. Check every extracted figure against the source document by hand. This is the step that matters, because at signature the error becomes yours.
4. Run a research question you already answered last season and compare the conclusion and the cited authority with your own work.
5. Amend one entity return and confirm the linked individual return updates, since multi-entity propagation is a core claim.
6. Record the credits consumed across the five, then multiply by your real return volume before signing an annual agreement.

The Accountability Question Nobody Has Settled

An agent that owns research, planning, preparation, filing and defence is doing considerably more than assisting, and the professional implications deserve stating.

The rules have not changed. A return is signed by a preparer, and that signature carries responsibility for accuracy regardless of what produced the figures. Penalties for an inaccurate return land on the taxpayer and, in some circumstances, on the preparer — never on the software.

That means the review obligation grows rather than shrinks as automation increases. When a person prepared a return, the preparer had reasoned through it; when an agent prepared it, the reviewer is seeing the reasoning for the first time, at volume, under the same deadline.

The word defence in the stated scope is the one to probe hardest. Supporting a position under examination means producing the authority and the workpapers behind it, which is genuinely valuable — but the representation before the IRS remains the professional's, and the practical question is what documentation the platform produces to make that defensible.

The security posture is the right shape: SOC 2 certification, IRS-authorised e-file provider status and BDO Alliance USA membership. Ask for the SOC 2 report itself and for written retention and deletion terms before client data moves, as you would with any system holding taxpayer information.

Instead: Scope, Filing And Structure