The work, described as problems

Built from scratch by our engineers, working independently. The engagement began before allgree existed and is still running.

Research advisory is a regulated product sold on trust, and most of it is published as a stock name and nothing else. The premise here was everything after that: entry, volatility, and exit. That is a harder product than a tip sheet. A recommendation has a lifecycle, subscribers are entitled to different parts of it, and every claim made about it has to survive a regulator reading it. There was no existing system to extend. It started as a conversation about what the product should be.

• Defined the product before writing it: what a recommendation is, what states it moves through, and who can see which of them
• Modelled the recommendation lifecycle as the core domain object, so entry, revision, and exit are the same record rather than three publications
• Built subscription and entitlement as product surface from the start, because retrofitting access control onto published content is where this category usually breaks
• Made the broker handoff one continuous journey, so the step from reading a thesis to acting on it isn't a copy-paste into another app
• Wrote the copy around methodology rather than performance, since the compliant claim and the honest one turn out to be the same claim
• Shipped in phases against a live audience rather than holding everything for one launch

Built from scratch for Park Loyalty by our engineers, working independently rather than in-house. The engagement began before allgree existed and is still running.

A permit is a small object with a lot of rules around it: who may hold one, where it is valid, when it lapses, and what enforcement sees when it is scanned at the kerb. The product carries eleven permit types, from residential and visitor through student, contractor, fleet, EV, and medical, and every agency words the eligibility rules differently while expecting the system to look like theirs. Getting it wrong is not a bad user experience. It is a citation somebody has to contest.

• Modelled the permit lifecycle (apply, issue, amend, renew, revoke) as explicit states, so eligibility and expiry were rules rather than scattered conditionals
• Built the motorist, fleet, tenant, and contractor journeys on one permit record instead of four parallel implementations
• Made permit types, eligibility, theming, and wording per-agency configuration, so onboarding a new agency is data rather than a branch
• Modelled the waitlist as ordered priority rather than a queue, because who gets the next residential permit is a policy decision, not a timestamp
• Treated the enforcement feed as the system of record for validity, since that is what the officer at the kerb is reading

Every country writes its e-invoicing mandate differently. Saudi Arabia's ZATCA, the UAE FTA, Malaysia's MDEC, and the Peppol network each want a different format, a different submission path, and a different definition of a valid invoice, and they change on their own timetables. A business does not want four integrations, it wants to keep sending invoices out of the ERP it already runs. Underneath that, an invoice rejected by a tax authority is not a failed API call, it is a compliance problem with a date attached.

• Modelled one canonical invoice and treated each jurisdiction as an adapter over it, so a new mandate is a new adapter rather than a new product
• Ran validation before submission rather than reading rejections back, because the tax authority is a slow and unforgiving test suite
• Designed the integration layer around retries and idempotency, since a duplicate invoice is worse than a late one
• Reconciled tax calculations against the source ERP rather than recomputing them, so the invoice and the books cannot disagree
• Handled auth, roles, retention, and audit trails as product surface, because data residency and a security review are entry requirements in these markets

The customer scans a code on a table and expects a menu in under a second, on whatever phone and whatever network they walked in with. Everything after that (cart, order, payment) has to work the same way for a merchant with four items and one with four hundred.

• Treated first-paint on a mid-range phone over mobile data as the hard budget, not an aspiration
• Made the menu render server-side so the scan-to-menu path never waits on client hydration
• Built cart and order state to survive a backgrounded tab and a dropped connection mid-payment
• Kept the merchant-facing catalogue simple enough to be edited by someone running a counter

Offers stack, conflict, expire, and apply only to some cards, some banks, some carts. Every one of those rules has to be evaluated while a customer is staring at a payment screen, and the answer has to be explainable afterwards when someone asks why a discount didn't apply.

• Separated offer definition from offer evaluation, so campaigns could be changed without a deploy
• Made precedence and conflict resolution explicit rules rather than emergent behaviour
• Set a latency ceiling for evaluation and treated exceeding it as a bug, not a tuning task
• Logged the resolution path per checkout, so a disputed discount has an answer

A voice agent is judged on everything except the model. The product targets a sub-500ms response budget, because a caller reads anything slower as a dropped line and starts talking over it. On top of that it has to know who is speaking, stop cleanly when interrupted, hand off to a person before the caller gives up, and reach whichever CRM, calendar, or helpdesk that particular business happens to run. It also has to survive a healthcare or finance security review, which rules out treating recordings and transcripts as an afterthought.

• Built the call loop around turn-taking, barge-in, and speaker diarization before tuning any prompts
• Treated the response budget as a hard ceiling rather than a target, and measured it per call rather than on average
• Kept speech-to-text and voice synthesis behind one interface, so a provider can be swapped per agent without touching the call loop
• Kept a defined escalation path, so the agent transfers to a human rather than improvising when it isn't confident
• Made tool calls the integration surface, so a new destination app is configuration rather than code
• Handled recording, transcription, and audit logging as product surface, because the regulated verticals ask for them first

A two-sided marketplace where both sides are on a phone and one of them is usually driving. Listings are geographic, availability changes by the hour, and the whole thing is worthless if search doesn't return the spot two streets away before the driver gives up and circles the block.

• Built search around location and time-window availability rather than a flat listing feed
• Kept host listing creation short enough to finish standing in the driveway
• Modelled booking state so a spot can't be double-sold across two devices
• Used a managed backend for auth, storage, and realtime, to keep the team on the product surface

Two products with opposite constraints on one data model. The merchant side is the screen somebody has open all day, mostly long tables of stock, orders, and reporting, where the failure mode is not an ugly page but a page that takes four seconds to filter. The customer side is the opposite: loyalty only works if the balance can be found and spent at the counter without holding up the queue, in about two taps, on both platforms. Points earned in the app have to be spendable at the till and visible in the dashboard, so neither side can own the truth alone.

• Kept the loyalty balance authoritative on the server, with the app showing a clearly-marked stale value rather than a wrong one
• Designed the counter flow first and built the rest of the customer app around it
• Built the merchant tables against realistic row counts, with server-side filtering and pagination from the start
• Made order state changes optimistic where safe and explicit where money is involved
• Put the analytics queries behind pre-aggregation rather than computing them per page load
• Kept one component library per platform, so the tenth screen matched the first and parity stayed cheap

Internal tools get built last and used most. The people using these were doing the work on paper and in a shared sheet, which meant the operational truth lived in someone's head and broke whenever that person was away.

• Watched the existing manual process before designing anything, including the steps nobody documented
• Built for the actual conditions of use: one hand, in a hurry, sometimes without signal
• Kept the data model close to how the team already talks about the work, so training was short
• Shipped the first tool narrow and complete rather than both tools half-finished