Kaji turns tax returns, rent rolls, appraisals and bank statements into validated data,
decisions and actions, on top of the systems you already run, and learns from every reviewer correction. No
rip-and-replace.
Property RightsFee Simplebbox [220,296,318,310]⚑ route to reviewer
09:41:02ingest AOI - Harborview Properties LLC.pdf → Articles of Organization
09:41:05extract 12 fields · every value linked to page + bbox
09:41:06validate 12/12 passed · pushed to system of record
Every file tracked from ingestion to review. Every value linked back to its source.
The operating bottleneck
Manual processing consumes capacity.
Critical lending processes depend on information that arrives unstructured, inconsistent
and difficult to operationalize. People fill the gap.
Shifting underwriting teams from data keyers to capital allocators.
The intelligent workflow layer
Kaji runs the credit workflow on top of your existing systems.
Your origination and servicing core stays the system of record. Kaji pulls documents in
through APIs, handles the manual work in between, and pushes validated data back. See how it connects →
01
Intelligent data ingestion
Tax returns, audits, rent rolls, appraisals and property data are classified and extracted as soon as
they arrive, whatever their format.
Auto-spreading and cross-document calculations: NOI, DSCR, LTV, LTC, debt yield, reserves and any other
ratio your credit policy defines, built from rent rolls, operating statements, appraisals, notes and
bank statements, with every input traced to its source page.
Every loan is checked against your credit policy, investor guidelines and covenant terms, both at
underwriting and throughout the life of the loan. Exceptions are flagged with the evidence behind them.
Every extracted value carries its source page and bounding box. Reviewers mark the value and the box
correct or incorrect, so review is fast and defensible.
Each time a reviewer confirms or corrects a value or its bounding box, that decision is captured and
used to retrain the models. Your models are tuned to your own documents, workflows and requirements, and
get more accurate with every file you process.
Ratios built from every document in the file, not just one.
Underwriting math rarely comes from a single document. Kaji assembles each input from
the rent roll, operating statement, appraisal, note, tax bill, insurance declarations and bank statements,
then calculates NOI, DSCR, LTV, LTC, debt yield, reserves and any other ratio your credit policy uses. Every
input stays linked to its source page, so every result can be traced and defended.
Examples shown. Also:global DSCRglobal cash flowDTIcap
rateARV-LTVbreakeven occupancyCLTV+ any formula your credit policy defines
--:--:--calc 10 documents · 14 inputs extracted · each linked to page + bounding box
Every ratio shows its inputs, and every input shows the document and page it came from.
Policy & guideline compliance
Your rules, applied to every loan, with the evidence attached.
Upload your credit policy, investor guidelines and covenant terms as they are, even as
a spreadsheet of questions. Kaji maps each rule to the document types and extracted fields it needs,
evaluates it on every file, and sends exceptions to an underwriter with the source evidence attached.
--:--:--rules 269 rules loaded · mapped to document types and schema fields
Your rules, applied the same way on every file. Every pass and every exception is traceable
to the page it came from.
Works with your systems
Kaji doesn't replace your loan origination system. It feeds it.
Your LOS, servicing core and other systems of record stay exactly where they are. Kaji
pulls documents from any API-accessible source, handles extraction, validation, rule checks and review, then
pushes the results back to your system of record through its API: model output and every human decision, with
the evidence attached.
kaji — integration · API in, API out · loan 202604492↓pull · documents↑push · data
Your document sources
▣LOS document folder
▤Document management system
◫Borrower portal
☁Cloud storage
any source with an API
API · GET
Kaji workflow layer
ingest & classify
extract · evidence-linked
calculate & apply rules
human review
package results
API · POST
Your system of record · LOS / servicing core
Loan 202604492waiting for
Kaji…
BorrowerHarborview Properties LLC
Loan amount$412,500
ProgramDSCR rental
fields written by Kaji
Latest API payload · POST /loans/202604492
// waiting for the first push…
--:--:--connect authenticated · document sources and system of record reachable
API in, API out. Your system of record stays the system of record, now with the evidence
behind every value.
What stays the same
Your LOS, servicing core and data warehouse remain the systems of record
Your team keeps working in the screens it already knows
No data migration, no rip-and-replace
What Kaji writes back through your API
Extracted values, each linked to its source document, page and location
Cross-document calculations such as NOI, DSCR, LTV, debt yield and reserves
Rule results and exceptions, with the evidence behind them
Reviewer confirmations and corrections
Audit trail entries for every value and decision
From evidence to action
A traceable path from source document to system update.
Kaji doesn't just generate an answer. Each step leaves a record you can audit, and every
human decision is fed back to make the next extraction better.
01Source documents
02Extraction
03Validation
04Business rules / models
05Human review
06Action / system update
↺ reviewer corrections feed back into extraction: the models
learn continuously
Human review → continuous learning
Every review sharpens the model.
Confirmations and corrections feed straight back into training, so the next file needs
less of both.
kaji — review · Uniform Residential Appraisal Report · R26-000111✓confirmed✎corrected↻sent to training
BoundariesNorth and West by the Allegheny
River, South by New Kensington-East
Dimensions28.12x120x37.10x120Area3913 sfZoningR2
Market ConditionsThe general marketing
conditions of this neighborhood are typical. Supply and demand factors appear to be in
balance…
City · p.2
Annotation fields0/8 reviewed
CityPage
2Box drawn ✓
New Kensington
Data value
Bounding box
extract
review
correct
retrain
corrections → training0
modelv1.14
field accuracy97.6%
--:--:--review session opened · 8 fields · evidence-linked
Confirm or correct, value and box. Every correction is captured, versioned, and used to
retrain your models.
Case study · business purpose lender
Same standards, less manual effort, faster decisions.
Kaji runs in production at a business purpose lender for underwriting and QC.
-70%
Outsourced analyst headcount
40before
12with Kaji
-4 days
Time to complete a loan
9before
5with Kaji
98%+
Field-level extraction accuracy
25,000+ documents processed
100% of values linked to source evidence
Exceptions routed to human review
Before · manual, outsourced
~40 outsourced analysts checking documents and keying data
Manual QC on every file
~9 days on average to complete a loan
With Kaji · automated, evidence-linked
Outsourced analysts down ~70%, to ~12
Ingestion, data entry and QC checks automated, with human review
~5 days to complete a loan: 4 days faster
“Kaji cut our reliance on outsourced analysts and gets loans through underwriting days faster.”
Illustrative figures for discussion; replace with client-verified data before external
use.
Why Kaji is different
AI calibrated to your institution, plus automation of your business rules.
Capability
Kaji
Generic LLMs
Legacy systems
Custom model fine-tuning
✓ Yes
✕ Not purpose-built
✕ No
Evidence-linked extraction & validation
✓ Yes
✕ Not turnkey
✕ No
Cross-document financial calculations
✓ Yes
✕ Not turnkey
✕ No
Turnkey managed execution
✓ Yes
✕ No
✕ No
Governance & control
Built for regulated lending environments.
01
Data protection
Encryption in transit and at rest, role-based access controls, and client data isolation.
02
Full auditability
Every extracted value links back to its source document.
03
Human in the loop
Reviewers validate exceptions before any action or system update.
04
Compliance alignment
Designed to support lender audit, vendor-risk and model-risk reviews.
Data governance & observability
Every value on record traces back to its source.
Pick any value in your system of record and follow its lineage: the source document,
the page and exact location, the model version that extracted it, the reviewer who confirmed it, and when it
was written. The link can be checked at any time and the result is logged, so an auditor can see it for
themselves.
--:--:--audit trace requested · 7 values on record
Nothing on the record without a source. Every link is checkable and every check is logged.
About Kaji Mindworks
Built by lending technologists and AI specialists.
Kaji Mindworks builds AI automation for the document-heavy work behind lending
decisions: underwriting, QC, policy compliance and covenant monitoring. We work with business purpose,
commercial and mortgage lenders, and with the capital markets firms that buy and securitize their loans.
Our team brings more than 65 years of combined experience in machine learning, lending
technology and mortgage capital markets. We run Kaji as a managed service on top of your existing systems.
We calibrate the models to your documents, apply your rules, and measure results against your own baseline.
鍛冶Kaji is Japanese for smithing: shaping raw metal into
something useful. We do the same with raw loan documents.
Company
Kaji Mindworks LLC
Focus
AI automation for lending operations
Delivery
Managed service, API-integrated with your LOS and servicing systems
Contact
hello@kajimindworks.com
The team
AI/ML and lending technology, in one team.
Hiro Hikawa, Ph.D.
Technology Development Lead
25+ years of experience in AI/Machine Learning, designing
and building enterprise applications powered by proprietary AI/ML algorithms, which helped financial
institutions turn complex data into accurate predictions and better-informed decisions.
Education Ph.D. in Statistics, The George Washington University
25+ years as a technical SME in software design and implementation, setting the strategy for system
functionality and enhancement requirements.
Education B.A., Boston College
Disciplines Financial and regulatory technology, real estate valuation technology,
financial modeling, mortgage underwriting, due diligence, mortgage capital markets
Brad Davis
Subject matter expert
25+ years in mortgage capital markets and consulting, leading teams at major financial institutions and
boutique consulting engagements.
Education B.A., St. Mary's College of Maryland
Disciplines Mortgage capital markets, loan sales / acquisitions, securitization, due
diligence, operational workflow engineering, program management, underwriting, financial modeling
How we start
A focused pilot on your documents and your workflow.
Weeks 1–2
Scope
Select one workflow, underwriting spreading or QC. Baseline current time and cost.
Weeks 3–8
Pilot
Run Kaji on your loans. Compare cycle time, manual effort and accuracy to the baseline.
Week 9+
Scale
Move to production alongside your existing systems. Extend to policy & guideline compliance,
including covenant monitoring.
Next step: a 30-minute working session to scope your pilot.