AI copilot built in Data validation · Reconciliation · Data quality

Validate anything.
Miss nothing.

AI finds it — you confirm it. Human-in-the-loop by design.

Start free Book a demo

Try it free for 7 daysFULL ACCESS

Connect CSV, Excel, databases & APIs — no code required

Reconciliation

500,000 rows × 200 columns^**

reconciled in minutes.

Auto-detecting keys · matching records…

●498,200 matched · 1,800 breaks flagged

** Enterprise plan — throughput varies with data, format & connection.

Data Quality

12 columns · 240,000 cells

scored in seconds.

Scoring 10 quality dimensions…

●Quality score 98% · 3 anomalies found

Data Lineage

3 systems · Trade → Settlement → Ledger

traced to the break.

Following the hand-offs across systems…

●Break −200 — broker fee posted to Ledger only

No code. No automation engineer. No ticket. One tool for every validation.

Validates Reconciliation breaks Completeness Uniqueness & duplicates Format & validity Anomalies Schema drift

The AI agent

An AI agent that does the checking for you

Not a chatbot bolted on. A working agent that drafts the rules, proves the numbers on a real engine, learns your data, and asks you before anything counts.

Describe it in plain English

Tell the agent what to check. It drafts the validation rules for you — no formulas, no code, no ticket.

Proposes — never guesses the number

The agent authors the rules; a deterministic engine computes every result. Exact and repeatable, never hallucinated.

Learns your data

Dataset Memory remembers the rules that worked, per dataset, and brings them back the next time you run.

Human-in-the-loop

You confirm, edit or remove any rule before it counts. The agent proposes — you have the final say.

Self-corrects

If the result isn't what you expected, the agent proposes a fix in plain English — you approve it, then save it.

Runs on a schedule

Set it once and the agent re-runs the checks on its own, then delivers the result to your inbox.

How it works

From raw files to a trusted result in three steps

Connect or upload

Drop in files or pick a saved connector — a database, an API, a spreadsheet. No pipeline to build. Don't see your connector? We're happy to add it.

Set the rules, or let AI draft them

Whatever you're validating, the rules are inferred for you. Tweak anything yourself, or just describe what you want in plain English — the AI copilot drafts the rules and refines them until the result is right.

Get results and reports

See matches, breaks, and a quality score — on demand or on a schedule, delivered to your inbox.

See it in action

Watch the AI work, live

Real walkthroughs, start to finish — AI BA rulebook drafting, reconciliation, data quality, data lineage, any-language document compare, and web extraction.

Reconciliation, liveConnect your sources, run the check, see every break.

AI BA — your AI Business AnalystPoint at a dataset — get a draft validation rulebook in seconds. You review and sign off.

Data quality, liveDrop a file — scored across 10 dimensions, with fixes.

Data lineage, liveTrace any number across every system — every hop, every break.

Any language, liveSwitch the whole app to your language — validate end to end.

Web extract, liveTurn any screen you can open into a validated data source.

Solutions

One platform, every data check

From a two-file reconciliation to full pipeline validation. Scan for the check you need — and if it isn't here yet, just ask.

🔀Reconciliation & integration

Data reconciliationMatch records across sources; every break flagged automatically, keys inferred.

Cross-system reconciliationTie out three or more systems in a single pass, not just a pair.

ETL / ELT validationConfirm the target matches the source after every transform.

Data integration testingProve a new feed or pipeline lands the data correctly before go-live.

Migration validationOld system vs new — nothing dropped, duplicated, or quietly changed.

Environment & rule driftCompare DEV / UAT / PROD; confirm rules and mappings still match.

Doc & PDF compareCompare two PDFs or documents line by line — flag matched, added, removed and changed lines.

🔎Structure, quality & lineage

Data quality scoringCompleteness, uniqueness, validity and anomalies — graded over time.

Freshness / SLAFlag records older than your timeliness window — 7d, 24h, or any age.

Data profilingStructure, distributions and problem columns at a glance.

Schema & structure driftCatch new, missing, renamed or retyped columns before they break a job.

Referential integrityEvery record has its parent key — no orphaned rows across tables.

Data lineage — trace a breakFollow a difference across systems to the hand-off where it started.

Format parsing → clean tableAny format — CSV, Excel, JSON, fixed-width — into clean, ready rows.

🧩Rules & governance

AI BA — your AI Business AnalystPoint at a dataset; AI drafts a validation rulebook across business, operational, technical and risk & compliance. You review and sign off — then it powers validation and exceptions.

Waterfall logicApply precedence rules and confirm the right outcome wins.

Category / classificationAI classifies records; anything unmapped is flagged for review.

Custom rule validationYour own business rules, checked deterministically every run.

Cross referenceLook values up across datasets and confirm they agree.

Governance & PIIOwnership, sensitivity and PII detection, all in one place.

Don't see your check?

New validations — control-total / row-count recon, statistical data drift, report tie-out, fuzzy dedup — are added on request, usually within a week.

Request a check →

The question everyone asks

Why not just use ChatGPT or Copilot?

It's the first thing people ask — so here's the honest answer. A chatbot is built for language, not exact math. The moment your data has to be right, three things quietly break: correctness, security, and repeatability.

	Web LLMCopilot / ChatGPT	AI DataValidator
Correctness	✕Can miscount or hallucinate	✓Deterministic engine — exact
Data size	✕One pasted file, size-limited	✓Files, databases & APIs at scale
Security	✕Sensitive data leaves your walls	✓Isolated & private — self-host in your environment^*
Repeatability	✕A different answer each time	✓Same rules, every run, scheduled
Audit trail	✕None	✓Every run logged with evidence
Rules	✕Re-typed in each prompt	✓Saved, versioned, reusable
Integration	✕Can't reach your systems	✓Connectors, scheduling, reports
Cost	✕Per-token — climbs with every run	✓Engine does the math — predictable

AI proposes the rules. A real engine proves the numbers.

* Runs fully in your environment on the Enterprise (self-hosted / on-prem) plan. Hosted plans keep your data isolated per tenant and never use it to train a model.

From the founder

I spent years doing this by hand

For years I worked across data operations, business analysis, data quality, mapping validation, integration testing, and automation. The same task followed me everywhere: someone needed data checked — a load verified, two systems reconciled, a mapping confirmed — and it landed on me.

So I did it by hand. Spreadsheets, scripts, evenings spent tying out numbers — then doing it all again the next day. Automating any of it meant a ticket, an engineer, and a wait.

I built AI DataValidator to be the tool I always wished I had: one place to validate anything — no code, no dependency — and automate the checks that repeat.

RavindraFounder · Data Ops · BA · Data Quality · Mapping Validation · Integration Testing · Automation Connect on LinkedIn

Pricing

Start free — no card.

Start with Reconciliation free for 7 days — no card. Upgrade to Solo for all 19 validations, connectors and automation, or go Enterprise for teams and regulated environments.

Our objective — and what makes it different

Where AI DataValidator is headed, and the ideas that make it work. Have a question? Ask the AI assistant below.

Objective.

Make trustworthy data validation something anyone can do — in minutes, with no code, no automation engineer, and no waiting on a ticket — in the language they think in. Every important number deserves an independent check before it's trusted; we put that check in the hands of the people who own the data. One application for every kind of data validation — so teams can retire the patchwork of separate tools, scripts and spreadsheets they juggle today.

Instant

Connect

Validate

Automate

Our goals

Self-serve for everyoneTurn a task that needs an engineer into a few clicks for a business analyst, QA or ops user.

One app, not tenEvery kind of validation — reconciliation, data quality, profiling, lineage, governance & PII, document compare and more (19 Solutions) — on a single engine, replacing a stack of separate tools.

Correct in any languageRun the whole app, and validate real-world data, in your own language and script — 8 today, more coming.

Trustworthy AIMake validation effortless with AI, without ever letting it invent a number.

Automated & hands-freeSchedule checks that run and report themselves, so validation keeps up as data grows.

What makes it innovative

01AI proposes, the engine provesThe AI reads your columns and a few masked samples, and drafts the checks in plain language; a deterministic engine then computes every number exactly and auditably. The AI never invents results — the automated four-eyes review that makes agentic AI safe for BFSI-grade data.

02Dataset Memory — human-in-the-loopCorrect a rule once and the system remembers your fix and re-applies it on every future run. The tool gets smarter with use, while you stay in control.

03Truly multilingual — tool and dataThe entire app switches into your language (right-to-left and all), and the engine understands non-English data too — accents, CJK, Arabic-Indic numerals, European number and date formats — so matches and totals stay correct across scripts.

04Any screen → a validated sourceBrowser-based Web Extract turns any screen you can open into an automated, validated data feed — a connector built for the analyst, QA or ops user who only has UI access.

05Self-serve by designNo integration project, no code, no approval workflow — from a two-file reconciliation to full pipeline validation, operable by a non-technical user.

06Your data stays yoursThe full dataset never leaves your server — a deterministic engine computes every result locally. The AI only ever sees column names and a handful of PII-masked sample values, and only to suggest rules. Regulated data can be locked to zero-retention providers.

Validate anything.Miss nothing.