A closer look at how dedicated TechOnHire teams have solved real engineering problems — from reconciliation engines in fintech to a Power BI layer that replaced fifteen hours of manual reporting a week.
Manual, spreadsheet-based reconciliation across three payment rails was turning month-end close into a two-week fire drill — and a growing audit risk.
Finance manually matched transactions across card, ACH and wallet rails every month. Mismatches surfaced late, close took up to nine days, and the process couldn't survive a SOC 2 audit unchanged.
A dedicated team built an event-driven reconciliation engine with automated ledger matching, exception queues for real mismatches only, and a full audit-trail dashboard integrated with the client's core banking APIs.
Month-end close dropped from nine days to 36 hours, reconciliation errors fell 92%, and the client passed its next SOC 2 Type II audit with zero exceptions on the reconciliation process.
"Quality that's already proven and support that doesn't stop at launch — exactly what we needed post-go-live."
CTO · Fintech Scale-upA logistics SaaS platform's deploys had slowed to a crawl — every release meant a full regression pass and a two-hour deployment window, no matter how small the change.
Orders, inventory and routing logic all lived in one Rails monolith. A single failing test anywhere could block every team's release, and deploys had become an event the whole company scheduled around.
The dedicated team peeled off domain services — orders, inventory, routing — behind an API gateway, containerized each with Kubernetes, and rebuilt CI/CD so services could deploy independently, alongside the client's in-house engineers.
Deploy time fell from two hours to twelve minutes, release frequency went from weekly to daily, and production incidents dropped 40% now that a single service's bug couldn't take down the whole platform.
"Ramp-up was faster than hiring a single contractor would've been, for several times the headcount."
Head of Product · Logistics PlatformA pre-seed B2B SaaS founder needed a working product demo in weeks, not months — without the codebase turning into throwaway prototype scaffolding the moment the round closed.
A scoped-from-scratch build was estimated at roughly ten weeks — longer than the founder's runway to the next investor conversation allowed.
A senior full-stack developer and a UI/UX designer worked in tight, prompt-driven loops with AI coding assistants to scaffold screens, endpoints and tests fast — with every AI-generated diff reviewed and hardened by the developer before it merged. Nothing shipped unreviewed.
The MVP shipped in three weeks instead of ten. The founder used it to close their seed round, and the handover included test coverage and documentation — a codebase built to keep going, not a throwaway demo.
AI tooling accelerated scaffolding and iteration — it never replaced review. Every change was checked and hardened by the developer before merge, and the client owns the code outright.
"We stopped thinking of them as 'the outsourced team' after about a month. They're just on the team."
Founder · Pre-Seed B2B SaaSA multi-brand e-commerce group was making inventory and ad-spend decisions on week-old spreadsheet exports, manually pulled from four disconnected platforms.
Shopify, ad platforms, the 3PL and the ERP each told a different part of the story. Someone spent close to fifteen hours a week stitching them together by hand, and by the time a report landed, the numbers were already stale.
The team built automated ETL pipelines into a central warehouse, then a suite of Power BI dashboards — inventory health, CAC/LTV by channel, SKU-level margin — with row-level security per brand and a daily automated refresh, no manual export required.
Manual reporting time dropped to near zero, stockouts on top SKUs fell, and marketing spend was reallocated toward the highest-LTV channels within the first quarter of the dashboards going live.
"The daily updates meant I never had to chase anyone for a status. That alone was worth the switch."
VP Operations · Multi-Brand E-commerce GroupNo — these are illustrative of the shape of work dedicated teams typically take on. Engagements range from a single embedded specialist to a full multi-role team, across fintech, e-commerce, logistics, healthtech and B2B SaaS.
Yes, on request and where the client agrees — ask your consultant during the first call and we'll arrange it alongside your estimate.
AI tooling speeds up scaffolding and iteration, but a senior engineer reviews and hardens every change before it merges. Nothing generated ships unreviewed, and clients retain full ownership of the resulting code.
Most teams are sized, costed and onboarding within two to four weeks of your first call, depending on the roles involved.
Tell us what you're building — we'll come back with a team shape and an estimate, not a sales pitch.