Enterprise AIWtrospai
Sftwtrs.AI logoSFTWTRS.AI ENTERPRISE AI · WTROSPAI
WTROSPAI · 1 OF 5
2026 THEME · KNOWLEDGE GRAPHS

Automation that keeps compliance first.

Wtrospai is our advanced AI automation platform for organisations that cannot afford shortcuts. It takes on repetitive back-office work, from reconciliation to high-volume voice calls, while every action stays traceable and within policy.

1 · TRIGGER
2 · CHECK POLICY
3 · ACT
4 · LOG AND PROVE

Inside the platform

Connectors
ERP, warehouse systems, email, telephony, document stores and partner portals
AI agents
Read documents, place and answer calls, reconcile records and draft responses
WtrDB knowledge graph
Governed context on customers, suppliers, stock, documents and history

Platform capabilities and expected impact

Policy engine
Your rules, checked first
100% of actions checked
Complete audit trail
Who, what, when and why
50 to 70% less audit prep
Human approval steps
Sign-off where judgement matters
10 to 20% routed to people
Voice AI agents
Inbound and outbound, at volume
3 to 5 times more contacts
Document workflows
Invoices and forms, read for you
50 to 70% less handling time
Graph-grounded
Governed WtrDB context
20 to 35% more accurate

Use cases and expected impact

PAGE Explore
Operations
Logistics and stock reconciliation
50% or more faster cycles
PAGE Explore
Finance
Invoices and supplier onboarding
50 to 70% less effort
PAGE Explore
Voice AI
Outreach, service and leads
40 to 60% lower cost per call
PAGE Explore
Compliance and bids
Audit evidence and tenders
40 to 60% faster bids
IN PRODUCTION
Logistics and warehouse reconciliation automated for a power EPC company
AT SCALE
Very high daily call volumes, including a large state-wide public outreach campaign
Expected impact figures are typical ranges from comparable deployments; results vary by site.
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
Sftwtrs.AI logoSFTWTRS.AI ENTERPRISE AI · WTROSPAI · HOW IT WORKS
HOW IT WORKS
2026 THEME · KNOWLEDGE GRAPHS

Automation you can explain to an auditor.

Wtrospai handles repetitive back-office work through one disciplined loop. Every action is grounded in your knowledge graph, checked against your policy and recorded, so your team can stand behind it.

THE ARCHITECTURE
One loop for every task
Agents draw governed context from WtrDB, the policy engine checks each action before it runs, people sign off where judgement matters, and every step lands in the audit trail.
THE POLICY ENGINE
Policy before action
Your rules, limits and approval paths are written as policy, so the same checks apply to every agent, every time.
THE AUDIT TRAIL
What every record holds
Records are ready for auditors and for your own reviews, without anyone rebuilding the story afterwards.
EXPECTED IMPACTTypical ranges from comparable deployments; results vary by site
100% of actions checked
Policy is checked before any action runs
10 to 20% routed to people
Approvals wherever judgement or money is involved
20 to 35% more accurate
Agents act on governed facts from WtrDB
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
Sftwtrs.AI logoSFTWTRS.AI ENTERPRISE AI · WTROSPAI USE CASES
WTROSPAI · 2 OF 5 · OPERATIONS
2026 THEME · KNOWLEDGE GRAPHS

Reconciliation that runs itself, every day.

Logistics reconciliation
IN PRODUCTION · POWER EPC COMPANY
THE CHALLENGE

Dispatch records, transporter documents and customer receipts sit in different systems and inboxes. Teams match them by hand, often at month end, and mismatches surface long after material or money has gone astray.

EXPECTED IMPACT
▪ 50% or more faster reconciliation, run daily
▪ 60 to 80% of exceptions closed in the month
▪ 50 to 70% less audit preparation effort
▪ 50 to 70% less manual matching effort
HOW WTROSPAI HELPS
  1. Gathers dispatch records, delivery challans, lorry receipts, e-way bills and proofs of delivery from your ERP, email and portals
  2. Reads each document and links it to the right shipment, customer and vehicle in the WtrDB graph
  3. Matches quantities, dates and values across every record
  4. Sends each exception to its owner with the evidence attached, and follows up until it is closed
  5. Records every match and decision for finance and audit
CONNECTS TOERPEmailTransporter portalsWtrDB
Stock reconciliation
IN PRODUCTION · POWER EPC COMPANY
THE CHALLENGE

System stock drifts away from what is on the shelves. Receipts, issues, returns and transfers are recorded at different times by different people, so small gaps grow quietly until an audit or a stock-out exposes them.

EXPECTED IMPACT
▪ 95% or better stock record accuracy
▪ 20 to 30% fewer stock write-offs
▪ 40 to 60% fewer repeat variances
▪ 50 to 70% less audit preparation effort
HOW WTROSPAI HELPS
  1. Pulls system stock, movements and cycle count results every day
  2. Compares them item by item and location by location
  3. Explains each variance by tracing the movements behind it in the graph
  4. Proposes adjustments and posts them only after approval
  5. Tracks recurring causes so they can be fixed at the source
CONNECTS TOERPWarehouse systemHandheld scannersWtrDB
Also in operations: freight bill checks against agreed rates, expected to recover 2 to 4% of freight spend, returnable packaging balances with 30 to 50% fewer lost bins, and daily exception summaries for plant heads.
Expected impact figures are typical ranges from comparable deployments; results vary by site.
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
Sftwtrs.AI logoSFTWTRS.AI ENTERPRISE AI · WTROSPAI OPERATIONS · HOW IT WORKS
HOW IT WORKS
2026 THEME · KNOWLEDGE GRAPHS

Reconciliation that runs every day.

Both operations use cases follow one pattern: gather every record, link it in the graph, match it and send the exceptions to the people who can fix them. Here is what that looks like for logistics and for stock.

USE CASE 1 · LOGISTICS
Logistics reconciliation
Each document is read, linked to its shipment, customer and vehicle in WtrDB and matched every day. Exceptions reach their owners with the evidence attached.
USE CASE 2 · STOCK
Stock reconciliation
System stock and movements are compared item by item each day, and adjustments are posted only after approval.
WHY DAILY MATTERS
Month end, or every day
Small gaps are fixed while material and money can still be traced.
EXPECTED IMPACTTypical ranges from comparable deployments; results vary by site
50% or more faster cycles
Matching runs daily, so gaps stay small
60 to 80% closed in-month
Each exception arrives with the documents behind it
40 to 60% fewer repeats
Recurring causes tracked by item, location and shift
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
Sftwtrs.AI logoSFTWTRS.AI ENTERPRISE AI · WTROSPAI USE CASES
WTROSPAI · 3 OF 5 · FINANCE AND PROCUREMENT
2026 THEME · KNOWLEDGE GRAPHS

Every payment checked before it moves.

Invoice, order and receipt matching
THE CHALLENGE

Supplier invoices arrive by email in many formats. Matching each one against its purchase order and goods receipt takes hours, and small differences in price, quantity or tax slip through.

EXPECTED IMPACT
▪ 50 to 70% less invoice processing effort
▪ 80 to 90% fewer duplicate payments
▪ 100% of approvals within delegated limits
▪ 30 to 50% faster month-end close
HOW WTROSPAI HELPS
  1. Reads invoices from email and supplier portals, whatever the format
  2. Finds the matching purchase order and goods receipt note
  3. Checks quantities, prices, tax details and payment terms
  4. Clears clean invoices for payment within your approval limits
  5. Routes every difference to the buyer with a plain explanation
CONNECTS TOERPEmailSupplier portalsWtrDB
Supplier onboarding and verification
THE CHALLENGE

New suppliers send registration papers, tax certificates, bank details and quality certificates in every format imaginable. Missing or mismatched details delay first payments and open the door to fraud.

EXPECTED IMPACT
▪ 50 to 70% faster supplier onboarding
▪ 100% of bank detail changes checked before payment
▪ 90% or more of certificates renewed before expiry
▪ 50 to 70% less effort preparing supplier audits
HOW WTROSPAI HELPS
  1. Requests the right documents through a guided checklist
  2. Reads them and checks that names, registration and tax numbers agree
  3. Verifies bank details and flags risky changes for review
  4. Records certificate expiry dates and sends renewal reminders
  5. Creates the supplier record after approval, with evidence linked in the graph
CONNECTS TOERPEmailDocument storeWtrDB
Also in finance: vendor statement reconciliation, expense claim checks and courteous payment reminders, expected to bring collections in 10 to 20% sooner.
Expected impact figures are typical ranges from comparable deployments; results vary by site.
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
Sftwtrs.AI logoSFTWTRS.AI ENTERPRISE AI · WTROSPAI FINANCE · HOW IT WORKS
HOW IT WORKS
2026 THEME · KNOWLEDGE GRAPHS

Checks that happen before money moves.

Finance work rewards care. Wtrospai reads each document, compares it with what your systems already know and asks a person whenever something does not add up.

USE CASE 1 · PAYABLES
Invoice, order and receipt matching
Every invoice is matched against its order and receipt before payment. Clean invoices clear within your delegated limits; differences and duplicates go to the buyer.
USE CASE 2 · SUPPLIERS
Supplier onboarding
New suppliers are ready to trade sooner, and certificate expiry dates bring renewal reminders on their own.
FRAUD CHECK
Bank detail changes
A request that does not fit the supplier's history in the graph is flagged before any money moves.
EXPECTED IMPACTTypical ranges from comparable deployments; results vary by site
50 to 70% less invoice effort
Clean invoices clear without waiting in a queue
100% within your limits
Approvals follow your delegated authority
80 to 90% fewer duplicates
Duplicates and bank detail changes checked against history
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
Sftwtrs.AI logoSFTWTRS.AI ENTERPRISE AI · WTROSPAI USE CASES
WTROSPAI · 4 OF 5 · VOICE AI
2026 THEME · KNOWLEDGE GRAPHS

Conversations at scale, handled with care.

Public outreach campaigns
AT SCALE · STATE-WIDE CAMPAIGN
THE CHALLENGE

Reaching very large audiences quickly, respectfully and on message is hard with call centres alone, and consent and outcomes are easy to lose track of.

EXPECTED IMPACT
▪ 3 to 5 times more contacts per day
▪ 100% of calls on the approved script
▪ 40 to 60% lower cost per contact
▪ Calls within TRAI rules: DLT registration, 140 and 1600 number series and DND checks
HOW WTROSPAI HELPS
  1. Scripts, permitted topics and calling hours approved before launch
  2. Calls placed at very high daily volumes, with natural conversations that capture each response
  3. Opt-outs honoured at once and consent recorded under DPDP for every contact
  4. Live dashboards of reach, responses and follow-ups for organisers
Customer service and appointment lines
THE CHALLENGE

Callers wait in queues for simple answers, after-hours calls go unanswered and skilled staff spend their day on routine requests.

EXPECTED IMPACT
▪ 24x7 cover, with every call answered
▪ 60 to 80% shorter waits for callers
▪ 40 to 60% of routine calls handled end to end
HOW WTROSPAI HELPS
  1. Answers around the clock and handles routine questions, bookings and changes
  2. Looks up orders, appointments and accounts in your systems
  3. Hands over to a person, with full context, whenever judgement is needed
  4. Summarises every call into your CRM or ticketing system
Lead qualification and follow-up
THE CHALLENGE

Enquiries go cold when nobody calls back quickly, and qualification varies from one salesperson to the next.

EXPECTED IMPACT
▪ Under 5 minutes to a first response
▪ 20 to 30% more qualified meetings
▪ 30 to 40% more selling time for the team
HOW WTROSPAI HELPS
  1. Calls new enquiries promptly, while interest is high
  2. Asks qualifying questions agreed with your sales team
  3. Books meetings straight into calendars
  4. Updates the CRM and schedules follow-ups automatically
CONNECTS TOTelephonyCRMCalendarsTicketingWtrDB
Expected impact figures are typical ranges from comparable deployments; results vary by site.
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
Sftwtrs.AI logoSFTWTRS.AI ENTERPRISE AI · WTROSPAI VOICE · HOW IT WORKS
VOICE AI · HOW IT WORKS
2026 THEME · KNOWLEDGE GRAPHS

Natural conversations, clear rules.

Wtrospai voice agents talk with callers in real time, with every answer grounded in your knowledge and every action inside your policy. Here is what happens on a call, and the checks around it.

THE ARCHITECTURE
Inside a call
Each turn of the call passes through speech recognition, the agent and speech synthesis in real time. The agent draws context from WtrDB, stays inside your policy and writes the outcome to your systems.
CAMPAIGN SET-UP
Before any call goes out
Campaigns start only after your team approves the script, topics and calling hours, and each contact is checked for consent and DND preferences.
HANDOVER
When a person takes over
A caller who asks for a person, raises a complaint or needs a decision on money is handed over at once, and never has to repeat themselves.
EXPECTED IMPACTTypical ranges from comparable deployments; results vary by site
100% on approved scripts
Scripts, topics and hours approved before launch
60 to 80% shorter waits
Warm handover with the whole conversation
100% of calls summarised
Consent, outcomes and summaries kept
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
Sftwtrs.AI logoSFTWTRS.AI ENTERPRISE AI · WTROSPAI USE CASES
WTROSPAI · 5 OF 5 · COMPLIANCE, BIDS AND TRUST
2026 THEME · KNOWLEDGE GRAPHS

Automation your auditors will appreciate.

Compliance evidence collection
THE CHALLENGE

Before every audit, teams chase screenshots, logs and sign-offs across systems and inboxes, and the evidence goes stale again between audits.

EXPECTED IMPACT
▪ 50 to 70% less audit preparation effort
▪ 60 to 80% fewer evidence requests to busy teams
▪ 80 to 90% of gaps found before the auditor
▪ Works with our Unified Compliance Model, Explore
HOW WTROSPAI HELPS
  1. Maps every control to the evidence it needs across ISO 27001, SOC 2 and DPDP
  2. Collects evidence on schedule from systems and control owners
  3. Checks completeness and freshness, and reminds owners politely
  4. Files each item against its control in the graph, ready for the auditor
Tender and RFP responses
THE CHALLENGE

Tenders run to hundreds of pages, with eligibility rules, formats and deadlines that are easy to miss under time pressure.

EXPECTED IMPACT
▪ 40 to 60% faster bid preparation
▪ 30 to 50% fewer rejections on technicalities
▪ 50 to 70% of evidence reused for the next bid
HOW WTROSPAI HELPS
  1. Reads the full tender and extracts eligibility, scope, formats and dates
  2. Builds a compliance matrix against your capabilities and documents
  3. Assembles evidence packs from your document store
  4. Tracks clarifications, deadlines and submissions until the bid is in

Built for trust

Policy before action
Every step checked against your rules and limits first
People stay in control
Approvals wherever judgement or money is involved
Complete audit trail
Who, what, when and why, kept for every action
Your data, your tenant
Deployed in your cloud subscription or on premises
Privacy by design
Consent, purpose limits and retention aligned with DPDP
Independently tested
Red teamed by our Security and Trust practice, Explore
Every Wtrospai deployment starts with one workflow, measured against how it runs today, then grows as your team gains confidence in it.
Expected impact figures are typical ranges from comparable deployments; results vary by site.
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
Sftwtrs.AI logoSFTWTRS.AI ENTERPRISE AI · WTROSPAI TRUST · HOW IT WORKS
COMPLIANCE, BIDS AND TRUST · HOW IT WORKS
2026 THEME · KNOWLEDGE GRAPHS

Paperwork that keeps itself in order.

Audits and tenders both reward the organisation whose evidence is ready. Wtrospai keeps it ready, inside guardrails your auditors can follow from start to finish.

COMPLIANCE EVIDENCE
The evidence loop
Evidence is gathered all year round and filed against each control, so an audit becomes a review of what is already there.
TENDERS AND RFPS
From tender to submission
Gaps show up on day one, while there is still time to close them, and clarifications and deadlines are tracked until the bid is in.
GUARDRAILS
Built for trust, step by step
Every action is checked against your rules first, waits for a person where money or judgement is involved, and is logged in full. Deployments are red teamed by our Security and Trust practice.
EXPECTED IMPACTTypical ranges from comparable deployments; results vary by site
50 to 70% less audit prep
Collected all year, not the week before the audit
40 to 60% faster bids
Eligibility, formats and dates tracked for you
100% of actions checked
Every action policy-checked, every deployment red teamed
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore

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