Which of these sound familiar?

You'll recognise this if

• Credit exposure lives across Tally, spreadsheets, and people's memory
• A customer being over their limit is noticed only after the next order ships
• Group-level exposure across entities takes days to put together, or cannot be put together at all
• Margin per customer is estimated, not tracked

What we'd build

• One live view of what each customer owes, against their credit terms and limit
• Purchases and sales linked, so margin per customer is visible
• A group-level exposure view across entities
• Your accounting system stays where it is. The system reads from it

Built for a trading and distribution company selling on 30, 60, and 90 day credit terms.

• Credit management system walkthrough (video) (Live system, data blurred)

Usually comes next: Payment follow-ups that happen on their own Vendor payments checked against what was ordered and received

You'll recognise this if

• Reminders go out late, or not at all, when that person is busy
• Escalation happens only when someone notices a payment is badly overdue
• There is no record of who was followed up with, and when
• The overdue list is rebuilt by hand every week

What we'd build

• Reminders sent on schedule over WhatsApp and email, based on each invoice's due date
• Escalations that trigger when a payment slips past an agreed point
• Every follow-up logged against the customer
• An overdue list that is always current

Built for a trading and distribution company, as part of their credit management system.

Usually comes next: A live view of who owes what, and who is over their limit

You'll recognise this if

• Orders, goods receipts, and invoices are compared by hand
• Duplicate or excess payments are discovered at audit, not before payment
• Disputes over short supply depend on someone's memory
• Month-end is spent reconciling vendor accounts

What we'd build

• Each invoice matched against its order and the goods received
• Mismatches flagged before payment is released
• A short exception list for the accounts team instead of a full manual check
• A history of mismatches per vendor

Same shape as a payroll verification system we built: matching data across several documents and flagging only the exceptions.

Usually comes next: A live view of who owes what, and who is over their limit

You'll recognise this if

• Salary registers, bank statements, PF and ESI filings, and attendance records are cross-checked by hand
• Overtime, bonus, and leave encashment are hard to verify against what was actually paid
• Mismatches surface after payout, through complaints
• Statutory filings and actual deductions are not reliably compared

What we'd build

• Every payroll run cross-checked across all source documents
• Mismatches flagged: salary against bank credit, deductions against filings, overtime hours against payment, bonus declared against paid
• A short exception list for the payroll team, sorted by severity
• A record of how each exception was resolved

Built for a garment manufacturer with a large workforce.

Usually comes next: Licences, certifications, and audits that never catch you off guard Every statutory deadline tracked, with proof it was met

You'll recognise this if

• An expiring licence or certification is noticed late
• Audit schedules, submissions, and status live in email threads
• Before each audit, readiness is rechecked manually
• Findings from audits are tracked in separate spreadsheets and nobody is sure what was closed

What we'd build

• Reminders before every expiry, well ahead of the deadline
• One view of all audits: scheduled, ongoing, and closed, with documents submitted
• A readiness view for each upcoming audit, based on what is valid and what is not
• Findings tracked from open to closed, each with one owner

Same shape as two systems we built: payroll verification that flags only the exceptions, and payment follow-ups that remind and escalate against due dates.

Usually comes next: Every statutory deadline tracked, with proof it was met Payroll errors caught before they reach employees

You'll recognise this if

• Deadlines are missed or met at the last minute
• Proof of filing is spread across email and folders
• Nobody has one view across all entities
• Late fees and notices arrive before anyone notices the gap

What we'd build

• One calendar of statutory deadlines across entities
• Reminders to the right owner ahead of each deadline
• Proof of filing attached to each deadline once done
• A view of what is due, done, and overdue

Same shape as a payment follow-up system we built: reminders on schedule against due dates, with escalation when something slips.

Usually comes next: Licences, certifications, and audits that never catch you off guard

You'll recognise this if

• Someone spends part of every day just sorting email
• Important messages are found late
• The same kinds of email are handled differently depending on who reads them

What we'd build

• Every incoming email read and categorised as it arrives
• Each category routed to the right person or next step
• Items that need judgment flagged, everything else handled in its lane

Built for a venture education company, connected to a hiring system that builds a searchable candidate pool from incoming applications.

Usually comes next: Applications screened, so your team reviews only the exceptions Orders from WhatsApp and email, captured without retyping

You'll recognise this if

• A review queue that grows faster than the team can clear it
• Criteria are applied differently depending on who reviews
• Good applicants wait days for a decision

What we'd build

• Each application checked against your criteria as it arrives
• Clear approvals move forward on their own
• Anything that needs judgment is flagged for a person
• A record of why each application was approved or flagged

Built for a curated creator network that screens every applicant before approval.

Usually comes next: An inbox that sorts itself

You'll recognise this if

• Orders are retyped from chats, and details get missed
• Customers are asked the same clarifying questions again
• Nobody can see which orders are pending entry

What we'd build

• Orders read from messages and turned into a structured draft
• Missing details flagged before the order goes further
• Every draft confirmed by a person before it enters your system
• One view of orders received, pending, and entered

Same shape as an inbox triage system we built: read what arrives, classify it, and structure it for the next step.

Usually comes next: A live view of who owes what, and who is over their limit An inbox that sorts itself

You'll recognise this if

• The same customer appears in several systems, matched only by phone number
• Lead records hold little more than a name and a number
• Past customers who are due to buy again are not tracked anywhere
• Sales agents start every call without the history

What we'd build

• One record per customer, joined across the systems you already use
• Each lead enriched once, so the team works from the full picture
• Old enquiries and past customers surfaced when they are likely to be ready again
• Agents given the right list, with the context for each call

Same shape as a hiring system we built: every applicant captured and enriched once, and the best fits surfaced on demand.

Usually comes next: Sales notes that reach the CRM without anyone typing them

You'll recognise this if

• The CRM is updated late, or only before a review
• Follow-ups depend on each rep's own reminders
• Managers cannot see where each account stands without asking

What we'd build

• Voice notes and messages from reps turned into structured CRM updates
• Every update confirmed by the rep before it is saved
• Follow-ups sent on schedule over email and WhatsApp, based on each account's stage
• One view of the pipeline that stays current without chasing

Same shape as an inbox triage system we built: read what arrives, sort it, and put it in front of the right person.

Usually comes next: Old leads brought back, with one record per customer An inbox that sorts itself

You'll recognise this if

• Customer details and documents are collected differently every time
• Onboarding stalls when the person handling it is busy
• Credit terms are set before anyone has the full picture

What we'd build

• One standard form for every new customer, collecting the details and documents you need
• Each customer's record created once, and used by everything that follows
• Credit terms and limits set against a complete record from day one

Built for a trading and distribution company, as the first step of their credit management system.

Usually comes next: A live view of who owes what, and who is over their limit Sales notes that reach the CRM without anyone typing them

You'll recognise this if

• Load sourcing lives in calls, chats, and each branch's spreadsheets
• Management cannot compare how branches work with brokers
• Fleet movement is pieced together by phone

What we'd build

• Load sourcing captured from the channels branches already use
• One view of broker activity across branches
• Fleet movement visible to management without calling around

Built for a logistics company, as the first of three systems under one ongoing relationship.

Usually comes next: Vehicle maintenance requests handled through one chat Every tender tracked from opportunity to outcome

You'll recognise this if

• Requests get lost in chats and phone calls
• Status is checked by calling the workshop or the driver
• Nobody has one list of open maintenance work

What we'd build

• One chat where maintenance requests and status updates are logged
• Every request tracked from raised to done
• One view of open maintenance work across the fleet

Built for a logistics company, alongside its fleet visibility and tender systems.

Usually comes next: A shared view of how loads are sourced and how the fleet moves

You'll recognise this if

• Tender deadlines are tracked by memory or a spreadsheet
• Submission documents are scattered across inboxes
• Nobody has one view of which bids are open, submitted, or won

What we'd build

• Every tender logged from the moment it is found
• Deadlines and submission status tracked for each bid
• Outcomes recorded, so the pipeline shows what was bid and what was won

Built for a logistics company, alongside its fleet visibility and maintenance systems.

Usually comes next: A shared view of how loads are sourced and how the fleet moves Every statutory deadline tracked, with proof it was met