Engagement Methodology
Every burnt client asks the same question before signing: "Will you actually ship?" Fair question. Here is exactly how we work — scope, pricing shape, what we commit to, and what you don't pay for.
Paid discovery sprint: fixed price, 2–4 weeks. Walk away after if it doesn't fit.
We scope against shippable user stories, not man-days. A user story has a clear acceptance criterion: "A logistics dispatcher can reassign a route in under three clicks." We estimate how long it takes to make that true and testable — not how many hours a developer will sit at a keyboard.
That discipline matters because it forces clarity before a single line of code. It also means your project manager can track progress in plain language, not spreadsheets.
Every external API, ERP connector, or legacy database adds integration surface. Undocumented or poorly-maintained third-party systems add disproportionate time. We price this risk honestly upfront rather than absorbing it quietly mid-project.
DPDP, RBI data-localisation, SEBI audit-trail requirements — each adds non-negotiable engineering work. We account for the compliance layer in the discovery sprint so it doesn't surface as a surprise at go-live.
Replacing a monolith, migrating off an on-premise system, or grafting AI onto a 15-year-old codebase is slower than greenfield work. We say so in the discovery output so you can make a genuine build-vs-replace decision.
Every project is different. We offer four shapes so the contract structure matches the risk profile of the work, not a one-size template.
The smallest shippable slice of value — a working feature, not a prototype — before any larger commitment. You see how we work, how we communicate, and what our code looks like in production. We prove velocity and quality on real scope, not a showcase demo. Most long engagements start here.
Flexible scope within a pre-agreed budget ceiling. You can reprioritise stories sprint-to-sprint as learning emerges; we stop and report when we approach the cap so there are no invoice surprises. Right for projects where full scope isn't known upfront but budget tolerance is finite.
A dedicated engineering capacity on a monthly basis. You direct the backlog; we maintain a consistent sprint velocity. Retainers suit teams that have shipped their MVP and need ongoing development, AI-agent maintenance, or managed engineering bandwidth without headcount.
Where the problem is well-defined and the result is measurable — reduce underwriting cycle from 9 days to 3, increase order-match accuracy above 95%, reduce manual exception handling by 70% — we can structure part of the fee around hitting those metrics. Requires a discovery sprint first so both sides agree on the baseline.
These are not upsells. They are structural options that let you validate fit before a large commitment. We offer them because a project started on a wrong assumption is bad for both sides.
We produce three deliverables: a technical architecture document, a detailed estimate broken down by user story, and a risk register that names every dependency, assumption, and unknown that could affect delivery. You own these documents outright. If after reading them you decide not to proceed — with us or at all — that is a legitimate outcome. No pressure to continue.
This option answers the estimation question before you sign a build contract. It is the right starting point for any project above moderate complexity.
The smallest shippable slice of the full vision — a feature your users can actually use, not a staged demo — before you commit to the full build. At the end of this phase, you have working software in production, a clear picture of our velocity and code quality, and an informed view on whether to continue. Most clients do continue. That is not our goal; it is the natural result of delivering a good first phase.
After handoff, bugs and regressions are fixed at no cost for 4–8 weeks depending on project size. This is not a helpdesk clause. It means that if something we built breaks — including edge cases that only surface under real user load — we fix it without a new statement of work. Scope creep and new feature requests are separate; defects in shipped work are covered.
Not ready for a full project?
Start with a paid discovery sprint. Fixed price, 2–4 weeks. Walk away after if it doesn't fit.
Start with a paid discovery sprint →Transparent process, opaque numbers. Here is what we have removed from the invoice.
Cloud credits, software licences, and infrastructure costs pass through at actual cost. We do not take a margin on tooling. You can see the provider invoices.
You are billed for people who work on your project. Internal meetings, recruitment, training, and administrative overhead are not billed to client engagements.
Coordination, status reporting, and documentation are part of delivery — they are not billed as a separate line item on top of engineering hours. If it is not moving a user story to Done, it is not on your invoice.
Complex software — systems with multiple integrations, AI decision layers, compliance constraints, or legacy dependencies — fails most often not because of bad engineering, but because the delivery model wasn't designed for the complexity. Fixed-price projects with vague scope get descoped at the end. T&M projects drift. Teams get rotated. Founders get the B-team.
We built our engagement model specifically around complex operations software — the kind of project where a standard software-house quote is either dangerously low or vague enough to mean nothing. Our cloud, QA, security, and data capabilities are the delivery stack underneath every AI agent deployment we run — not separate services, but load-bearing infrastructure that makes enterprise-grade shipping possible.
The evidence is in the work. Our complex software success stories show what this looks like in practice: a supply-chain image-matching system at 99% efficiency gain, a BI platform pulling four AI models together with minimal human input, a D2C logistics stack that tripled organic traffic in four months.
None of those were straightforward builds. That is why we worked on them.
AI-native does not mean we add a chatbot. It means the core delivery model uses AI agents for code review, test generation, dependency analysis, and release monitoring — which compresses the QA and integration cycles that inflate estimates on complex software. That compression is what lets us hold a fixed price on work that competitors quote as T&M.
No black boxes. No quarterly check-ins on a multi-month project.
Architecture, integrations, compliance surface, risk register. Shared document — you see everything.
Stories written, estimated, and prioritised. You see the estimate by story so you can reorder the backlog before we start.
Working software shown every week — not screenshots. You test it. We take feedback. The backlog is live and visible throughout.
Documentation, runbooks, and 4–8 week warranty cover. Your team owns the codebase with no vendor lock-in.
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