Now building · Early access open
Every document checked. Every mismatch explained.
Aiverity reads invoices, certificates, statements and onboarding documents, compares each field against your records and sends only the inconsistencies to a reviewer, with a plain-language reason attached.
- Field-level extraction
- Cross-record comparison
- Human approval on every flag
- Auditable decision history
INV-7781.pdf · Page 1
SampleDiscrepancy found
PO reference on the invoice (55102) does not match the purchase order on file (55120). Routed to reviewer.
The problem
Document verification is still a copy-and-compare job.
Fintech onboarding teams, claims handlers, procurement and audit staff all verify the same thing: does this document agree with what we already know? Today that check is done by eye.
Manual re-keying
Analysts copy names, numbers and dates from PDFs into spreadsheets before they can compare anything. A single supplier file can take 30 minutes.
Checks across disconnected systems
The invoice is in email, the purchase order in the ERP and the certificate in a shared drive. Errors hide in the gaps between them.
No record of why
When an auditor asks why a document was accepted, the answer lives in someone’s memory or a chat thread.
Headcount scales with volume
More customers, claims or suppliers means more reviewers. Backlogs grow at quarter-end and onboarding slows.
The Aiverity approach
Let software do the extraction and comparison. Let people make the decisions, with the evidence laid out in front of them.
Platform capabilities
One workspace from upload to approved.
Aiverity is designed around the verification workflow itself, not a generic chat interface. Each capability feeds the next.
Document extraction
Pulls text, key-value pairs and tables from PDFs and scans, including invoices, incorporation certificates, bank statements, W-9s and claims paperwork.
Analysts stop re-typing data before they can start checking it.
Cross-record comparison
Matches each extracted field against the reference you choose: a purchase order, a vendor master, a policy record or another document in the same case.
Certificate
14 Dock Rd
Supplier form
41 Dock Rd
Mismatches between systems surface automatically instead of by chance.
Validation rules
Set the checks a document must pass, such as expiry windows, required fields, name matching tolerance or approved bank accounts.
Each team encodes its own policy once and applies it consistently.
Explained discrepancies
An AI model writes a short note for every flag: what differs, where it appears and whether it looks like a typo or a substantive conflict.
“Street number differs (14 vs 41). Postcode and director match, so this is likely a transcription error.”
Reviewers understand the issue in seconds without opening three files.
Review queue
Documents that pass every check can be cleared in bulk; anything flagged goes to a prioritised queue with assignment and status.
Reviewer time goes to the cases that actually need judgement.
Decision history
Every extraction, rule result, comment and approval is stored with a timestamp and the person who made it.
Audit and compliance questions have a documented answer.
How it works
Five steps. A person signs off on the last one.
- 01
Submit
Upload documents to a case or send them from an intake workflow. Files are stored encrypted and linked to the case.
- 02
Extract
Text, fields and tables are read from each page and normalised into structured data.
- 03
Validate
Fields are compared against reference records and your validation rules. Each check produces a pass, review or conflict result.
- 04
Explain
An AI model summarises each issue in plain language and suggests the likely cause.
- 05
Decide
A reviewer approves, flags or requests a new document. The decision and evidence are saved to the case history.
Interactive product preview
Try the verification workspace.
Search records, filter by workflow, open a case to compare fields side by side, and approve or flag it. This preview runs in your browser on fictional sample data.
Verified
3
Needs review
2
Discrepancies
2
Processing
1
Documents checked this week
CheckedFlaggedInsight
Most discrepancies this week come from supplier onboarding: address and registration fields typed manually into intake forms.
Who it’s for
Built for teams whose job is to say “this checks out.”
Fintech and payments
KYB onboarding teams
The challenge. Business customers submit incorporation documents, proof of address and ownership records that must agree with the application.
With Aiverity. Aiverity compares each document with the application data and flags expired or inconsistent evidence before an analyst opens the file.
Insurance providers
Claims intake and fraud review
The challenge. Repair estimates, medical invoices and police reports need to match the policy and first notice of loss.
With Aiverity. Policy numbers, VINs, provider IDs and amounts are cross-checked so adjusters focus on the claims that disagree.
Procurement organisations
Supplier onboarding and AP
The challenge. Supplier certificates, tax forms and invoices arrive in different formats and are checked against the vendor master by hand.
With Aiverity. Registration details, bank accounts and PO references are validated on arrival, reducing payment errors and onboarding delays.
Accounting firms and compliance teams
Audit evidence and internal reviews
The challenge. Bank statements and supporting schedules must reconcile with client records, with a documented trail for every conclusion.
With Aiverity. Extracted balances and entities are matched to the client’s records and every reviewer decision is preserved for the file.
Technology
How We Use Amazon Web Services
Aiverity’s platform architecture is designed on AWS around the verification pipeline: documents arrive through a secured API, are stored in Amazon S3, read by Amazon Textract, analysed with foundation models in Amazon Bedrock, and recorded in Amazon DynamoDB so every reviewer decision can be traced. Serverless components keep cost proportional to the number of documents processed while the product is being built.
Data Collection
Amazon API Gateway
Receives authenticated document submissions from the web app.
Secure Storage
Amazon S3
Encrypted object storage for source documents and reports.
Processing
AWS Lambda + Amazon Textract
Event-driven jobs extract text, fields and tables.
AI Intelligence
Amazon Bedrock
Compares fields and explains each discrepancy.
Application Experience
Amazon DynamoDB + Amazon Cognito
Case records, reviewer decisions and secure sign-in.
- Amazon S3: Stores uploaded business documents and generated verification reports as encrypted objects.
- Amazon Textract: Extracts text, key-value pairs and tables from invoices, certificates, statements and contracts.
- Amazon Bedrock: Provides foundation models that compare extracted fields, explain inconsistencies and draft reviewer summaries.
- AWS Lambda: Runs the event-driven steps of each verification job, from extraction to rule checks.
- Amazon API Gateway: Exposes the secured API that the web application uses to submit documents and fetch results.
- Amazon DynamoDB: Holds verification records, extracted fields, reviewer decisions and audit events.
- Amazon Cognito: Handles user sign-in, team membership and role-based access to workspaces.
- Amazon CloudWatch: Collects logs, metrics and alarms for processing latency and job failures.
Business progress
Join the early access program.
Where we are
Aiverity is building its initial product. The verification workflow, data model and AWS architecture are defined, and the interactive preview above shows the intended reviewer experience.
Early access
We are looking for compliance, onboarding, claims and procurement teams willing to share anonymised document types and review the workflow with us before launch.
What early partners get
Direct input into validation rules and integrations, priority onboarding, and a working session with the founder on their current verification process.
Request early access
Tell us about the documents your team verifies today.
Pricing
Simple plans per user.
Plans apply when the platform becomes available to early-access customers.
Starter
Small teams validating a single verification workflow.
$10/ user / month
- Document upload and extraction
- Field-level discrepancy flags
- Single review queue
- Verification history
Growth
Most teamsTeams running several verification workflows each week.
$20/ user / month
- Everything in Starter
- Cross-document record comparison
- Configurable validation rules
- Multiple reviewers and assignments
Enterprise
Compliance functions that need oversight across departments.
$30/ user / month
- Everything in Growth
- Role-based access controls
- Exportable audit trail
- Onboarding support
Team
The Team Behind Aiverity
Abdulraheem Hameedah
Founder
Abdulraheem founded Aiverity to give verification and compliance teams a structured, auditable alternative to manual document checks. He leads product direction, platform architecture and early-access partnerships.
Contact
Talk to the team.
Questions about the product, pricing or a partnership? Send a message or email us directly.