Fetch does not stop at configuring tools. When a redesigned workflow needs real software — an agent pipeline, a data platform, an operations system — the same team that ran your Sprint builds and operates it. Here is what that team has shipped.
Headquartered in Singapore with engineering hubs in Hanoi and Ho Chi Minh City. Our engineering clients have included a national defence organisation, a national media broadcaster, regulated digital-asset issuers, an ed-tech operator and family-run businesses modernising their operations.
Agentic AI, real-time voice AI, institutional ledgers, wearable-data platforms, edge-to-cloud IoT — most of it in production today, not in a lab.
Every build starts with a clickable mockup of your product and a PRD, iterated with you until sign-off. The proposal is written against what you approved.
AI agents draft, test, review and document inside a process our senior engineers design and gate. It changes the speed you experience; it does not change who is responsible.
Documentation, runbooks and test cases are produced alongside the code. When a fixed-scope engagement ends you receive a repository your team can operate.
Open a practice to see what it has shipped to production — described by capability, not by client name.
AI that does a job, not a chatbot demo.
LLM-powered products end-to-end: model orchestration, retrieval, evaluation, guardrails and the plain product engineering around them. This is the engineering that turns a Sprint's redesigned workflow into software your team uses every day.
Enterprises have moved from “try an LLM” to “run a workflow on one”. The differentiator is no longer the model — it is orchestration, evaluation, cost control and provider independence.
| Multi-agent orchestration | LangGraph agent pipelines for content generation (brand DNA + campaign brief → a week of copy, image and video drafts) and creator tooling with a node-based canvas editor |
| Model-agnostic LLM gateway | A Go gateway abstracting OpenAI, Anthropic, Gemini and ~9 further providers behind one typed API — structured output, model listing, per-tenant keys — so a client is never locked to one model vendor |
| Real-time voice AI | Live, speaker-diarised transcription of video interviews from a Chrome extension, with the backend acting as a short-lived token broker so secrets never ship to the browser |
| Document AI | Scanned exam papers → OCR → LLM / vision extraction → marking schemes → human reviewer UI, versioned assessment pipeline |
| AI scoring & ranking | Candidate-scoring service with per-role rule configs, replacing a classic-ML stack |
| Conversational bots at scale | Telegram bot for a national broadcaster on Azure OpenAI with separate deployments for reply, moderation and engagement, queued on Redis, CMS-managed |
| Meeting intelligence | AI assistant that joins and records calls and produces briefs — the tool our own team runs on |
| On-device ML | In-browser face analysis with MediaPipe, paired with LLM interpretation server-side |
The systems a business runs on — built to be operated, not just launched.
When the workflow redesign needs more than a configured tool, we build the platform: catalogue to dispatch, back office to payments, CMS to storefront.
Most operational pain sits in the gaps between systems. We build the connective tissue — and the admin tools that let your team run it without us.
| Operations platform | End-to-end ops platform for a fresh-produce retailer: catalogue and inventory → orders → dispatch → rider delivery. Admin web, customer storefront, rider app, NestJS backend; payment-provider cutover absorbed mid-programme |
| Back-office & payments | Back-office with Stripe payments, S3 documents and JWE-secured APIs; admin SPA |
| CMS & marketing sites | Headless CMS admin for a chat-bot product; corporate websites with small auth APIs |
| Ed-tech SaaS | AI mathematics tutoring platform with subscriptions, question bank, exam papers, transactional email and analytics; Kubernetes with GitOps |
| Content platforms | AI campaign-content engine and a two-sided brand-contest platform for AI video creators |
Data platforms that ingest from the physical world and turn it into decisions.
Wearables, sensors and scales — with the identity, consent, ingestion and aggregation done properly.
Wearables have crossed from gadgets into institutional programmes — defence, insurers, employers — and edge-plus-cloud patterns let small operators get plant-floor data into the cloud without a SCADA budget.
| Wearable data platform | Fitness and health data platform for a national defence organisation: ingestion from consumer wearables → aggregation → API and two web applications (participant and admin), national digital-identity (SingPass OIDC) login |
| Corporate wellness | Wearable fitness-tracking platform with roles, leaderboards and device integrations, now under a security-and-scale upgrade |
| Industrial IoT / edge | Cloud weighbridge: industrial scale → Raspberry Pi edge service (serial capture, offline queue, retry on reconnect) → realtime cloud backbone → capture / review / admin web and an OpenAPI ERP interface |
Digital-asset infrastructure for regulated and institutional use.
For financial institutions and licensed issuers: privacy-preserving ledgers, stablecoin issuance and on-ledger settlement, delivered to production.
Stablecoin legislation in the US, MiCA in the EU and MAS's framework in Singapore have moved tokenised money from pilots into regulated production. We are one of the few Asia-Pacific teams with production DAML delivery.
| Canton Network / DAML | DAML smart contracts on the Splice / Amulet token standard; validator and participant operation; CIP-56 fungible-token implementation with delivery-versus-payment and a compliance blacklist extension |
| Institutional exchange | Partner / liquidity-provider swap exchange on Canton: on-ledger atomic-swap escrow (84 scenario tests), partner API, indexing and fee crons, wallet provider, TypeScript trading SDK — live on mainnet |
| Stablecoin issuance | Three generations for one licensed issuer, from an EVM pilot to a Canton-based issuance and tokenisation console driving the full mint / burn / transfer lifecycle |
| Custody & treasury | Hot-wallet token-manager and withdrawal-manager microservices, cross-chain settlement, multi-tenant deployments |
Client names are withheld under NDA; each engagement is described by sector and year. References can be arranged on request.
Wearable ingestion → aggregation → participant and admin apps, SingPass OIDC login, dual CI with SAST and secret detection on every push. Fully containerised, no secrets in source.
Spreadsheets and chat replaced by one system from inventory to the rider's phone, delivered fixed-scope in a 16-week programme. Handed over August 2026 with a full handover pack; phase 2 scoped.
Chrome extension streams interview audio for diarised transcription; a scoring service applies per-role rules and LLM evaluation. Handed over to the client's own cloud in June 2026 and in production.
Reply, moderation and engagement on separate Azure OpenAI deployments, Redis job queues, editorial control from a CMS. Built to a container registry on every push.
Tutoring platform plus a separate multi-provider LLM gateway and OCR pipeline: the operator can switch or add models centrally without touching the student-facing app.
Raspberry Pi edge service reads the scale over serial, buffers offline and retries on reconnect; realtime cloud backbone; capture / review / admin web; OpenAPI interface for the ERP.
Every swap settles atomically on-ledger under Canton's privacy model; partner API and SDK for liquidity providers. Live on mainnet with Terraform-managed AWS infrastructure.
From EVM pilot to institutional issuance console on Canton with compliance controls — the most actively developed product in the 2026 portfolio.
Brand DNA + brief → a six-phase pipeline drafting a week of copy, images and video; a contest platform where creators compose AI video in a node-based editor driven by a LangGraph agent.
AI agents do the repetitive work of building software — drafting, testing, reviewing, documenting — inside a process our senior engineers design, direct and sign off at every gate.
It is not “AI writes the code and we ship it”. No line of code, deployment or document reaches you without a named engineer having reviewed and approved it. AI changes how fast and how transparently we work; it does not change who is responsible.
| Stage | Fetch |
|---|---|
| Before you commit | A clickable mockup of your product and a PRD, iterated with you (V1 → V2 → V3) until sign-off. The proposal is written against the versions you approved |
| Build | Engineers direct AI agents inside a nine-phase, gated pipeline. Every feature starts from a failing test; docs and test cases are generated alongside the code |
| Review | Seven-agent, two-track review on every feature. The code track fixes what it finds, capped at three cycles; the strategy track never auto-fixes — it escalates to a human. Security findings are never closed by an agent |
| Quality gates | Deterministic and blocking: test coverage, accessibility and touch-target checks, security lint on every change, a device beta before release. A skipped gate is recorded as skipped — nothing is silent |
| Handover | Architecture docs, runbooks, environment inventories and test cases exist from day one because the agents produce them as they work |
AI in how we build ≠ AI in what we build. AI features inside your product are scoped and priced like any other feature.
From a 30-day Sprint inside your operations to a senior squad inside your product team.
AI adoption inside existing operations: map, redesign, deploy, train, measure
Fixed scope, fixed price; 30 days to 18 months
Outcome-driven deliverables, adoption and time-savings measured, roadmap at handover
45-minute strategy call
A well-defined product or platform with a known total and a handover as the end state
Fixed fee against milestones with an objective Definition of Done for each
Explicit in-scope / out-of-scope lists; deemed-acceptance windows so nothing stalls; 30-day warranty after final acceptance
Discovery → mockup + PRD → proposal
A live product that keeps changing; ongoing capacity with no fixed “done”
Monthly fee for a defined capacity, billed in advance, 3-month minimum, 30-day notice
Response-time SLA by severity; rolling warranty; an indicative roadmap you steer each sprint
Post-handover of a build, or an existing product
You have the product team and need senior engineers inside it
Time and materials, monthly
Named engineers, replaceable with notice
Immediate
Commercial headlines. Currency SGD, prices exclude GST. Acceptance windows of 5 business days (Scoped) or 3 business days after a sprint demo (Retainer), then deemed accepted. IP in deliverables transfers on payment. Liability capped at fees paid. Third-party costs (cloud, SaaS, hardware) borne by the client and itemised. PDPA-compliant handling of personal data. The SoW / MSA controls. Security & data handling →
Ten layers, primary choices and what else is live. Not a wish-list.
| Layer | Primary |
|---|---|
| Backend | TypeScript — NestJS, Prisma, Node 22 |
| Web | Next.js, React, Vite SPAs |
| Mobile | React Native |
| AI / ML | LangGraph, Anthropic, OpenAI, Azure OpenAI, Gemini; multi-provider gateway |
| Ledgers | DAML / Canton (Splice, CIP-56) |
| Data | PostgreSQL, Redis, BullMQ |
| Identity & payments | Auth0, SingPass OIDC, JWT / JWE |
| Cloud & delivery | AWS EKS + ArgoCD (GitOps), Terraform |
| CI & quality | GitHub Actions, Docker, Helm |
| Messaging | Telegram, WhatsApp, web push |
Six technologies we expect to dominate the next 18 months, with production evidence for each.
The value has moved from “answer a prompt” to “complete a workflow” — with tools, memory and human checkpoints
Model prices and quality shift monthly; provider lock-in is now a board-level risk
Interviews, support calls, meetings — the audio layer of business is becoming data
Defence, insurers and employers are formalising health-data programmes — identity and consent are the hard part
Plant-floor data without a SCADA budget
US, EU and Singapore frameworks now in force; institutions are building, not piloting
Start with a discovery call. Within days you'll have a clickable mockup and a PRD of your product — before any commitment.
