Scalable, secure, and purpose-built. Our engineering team delivers high-quality code that powers your core business functions.
Engagements typically start from $5,000 USD. Final scope priced after discovery call.
Hangzhou-based, ex-Alibaba senior engineering team. Project rate $14k–$85k over 4–10 weeks. Three engineering commitments written into every contract before any code is shipped.
200+ reference cases with expected outputs and a CI-gated scoring rubric land in the first sprint — before any production code merges. Accuracy is measured from day one.
Six-month warranty on production fixes. Customer owns source code, deployment docs, and runbook from day one of handover — no vendor lock-in.
Token routing, caching, and model selection re-evaluated every 90 days against the eval set so unit economics stay predictable as traffic grows.
A fixed-price feasibility engagement. About one in four scopings recommends not building. Fee credits 100% toward a build engagement if you proceed.
We prioritize modularity and observability in every codebase. By adopting modern practices such as infrastructure-as-code and automated CI/CD pipelines, we ensure that your software is not just built for today, but ready for future expansion. Our development process includes rigorous security audits and performance profiling to ensure your users experience seamless interaction. Last updated: 2026-05-19.
Custom software is a broad category, so this page covers the engagements where we deliver well: complex products, integrations between systems no off-the-shelf SaaS connects, and AI-augmented features that need to live inside an existing application rather than as a standalone tool.
Most SaaS products that survive their first 18 months hit a wall: the MVP architecture cannot carry a 10x customer count, the data model assumed single tenancy, the auth layer was a stop-gap. We rebuild the foundation underneath the live product without breaking it — usually module by module behind feature flags — so the team that wrote the MVP can keep shipping features while we replace the load-bearing pieces.
Mid-market companies typically run on 80 to 150 SaaS products, half of which are paid for and half-used. We build internal platforms — operations dashboards, customer 360s, finance close tools — that consolidate the workflow into one system the team actually uses, with the SaaS products kept underneath as data sources rather than as the primary user surface.
Horizontal SaaS plays the volume game; vertical SaaS plays the depth game. We build vertical products for niches where the horizontal incumbents are 60% solutions: small accounting firms, independent law practices, regional logistics carriers, specialty manufacturers. The technical bar is the same as horizontal SaaS, but the workflow modeling is the moat.
Marketplaces are punishing because the technical complexity (matching, search, pricing, payment flows, dispute resolution) is married to a chicken-and-egg supply problem. We build the technical layer with the supply problem in mind: launch with a constrained category and a manual matchmaking process, automate progressively as liquidity arrives, and avoid the early over-engineering that kills marketplace burn rates.
Fintech and healthtech are not 'normal SaaS plus an audit'. The compliance layer changes architecture decisions: which cloud region, which encryption story, which data retention policy, which audit trail format. We build with the regulator in mind from week one — SOC 2, HIPAA, PCI, regional financial regulations — so the audit is a paper exercise, not a six-month rebuild.
Most teams want AI features inside the product they already have, not a separate AI tool. We build the AI surface as a first-class part of the product: inline copilots, smart defaults, document understanding, search-in-natural-language, with proper grounding, evaluation, and cost controls so the AI features do not silently blow the product's gross margin.
A custom software engagement moves through five phases. Phase length scales with project complexity, but the sequence is constant. The single biggest risk in custom software is starting the build before the architecture decisions are made, so we resist the temptation to skip the up-front phases even when timeline pressure is real.
We map the product surface, the data domain, the integration surface, the non-functional requirements (scale, latency, compliance), and the team that will own the product after we ship. Output is an architecture decision record naming every load-bearing technical choice — language, framework, database, deployment model, auth model — with the trade-offs spelled out so the choice is reviewable, not implicit.
Before we write feature code, we build the design system — typed primitives for the domain (entities, value objects, events) and the UI components those primitives drive. This pays back continuously: every subsequent feature is faster to ship, more consistent, and less likely to regress, because the foundation is shared.
Features ship in two-week increments behind feature flags. Each increment ends with a demo against the agreed acceptance criteria, a written changelog, and an updated architecture decision record if something material changed. We hold the line on test coverage, observability, and documentation per increment so the codebase ages well rather than accumulating debt under timeline pressure.
Performance profiling under realistic load, security review (SAST, DAST, dependency audit, infra review), observability dashboards, alerting tuned to the SLO, and a written runbook for the most likely incidents. Hardening is a phase, not an afterthought; products that skip this phase pay for it during the first real outage.
Launch happens behind a feature flag with a phased rollout plan. We stay attached for the first six weeks of production to triage real-world traffic, then transition to operate-with-you: monthly architecture review, dependency upgrades, security patching cadence, and a written escalation path so your team knows who to call when something breaks at 2 AM.
On a typical 24-week custom software engagement, here are the concrete checkpoints. Smaller projects compress these, larger projects extend the iterative phase — but every project hits the same checkpoints in the same order.
Every load-bearing choice — language, framework, database, deployment, auth, observability stack — written down with the trade-offs and the reason it was chosen. This is the document a future engineering hire will read on day one.
Typed domain primitives and the UI components they drive deployed in staging with a Storybook-style component preview, so feature work in the next phase moves quickly and consistently.
A complete vertical slice — sign-up to the first valuable action — running in production for internal users and a small set of pilot customers. This is the earliest point where real users can validate product decisions.
Every feature on the agreed v1 scope shipped to staging with passing tests, observability, and documentation. The product is ready for the hardening phase.
Performance profiled, security reviewed, observability tuned, alerting wired, runbook written, rollback plan tested. The product is ready for paying customers.
Customer traffic moved behind a phased rollout (1% → 10% → 50% → 100%) with health metrics gating each step. Operate-with-you handover complete.
Recurring questions from founders and CTOs evaluating us against in-house build, an alternative agency, or a generic outsourcing shop.
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