How long does it take to develop a web application?

Timelines vary based on complexity. An MVP can be ready in 4-8 weeks, while a full enterprise application may take 3-6 months. We use agile methodologies to deliver value from the very first weeks.

What technologies do you use for development?

We use modern technologies including React, Next.js, TypeScript, Node.js, Python, React Native, and Flutter. For AI, we work with OpenAI, LangChain, and custom models. Our infrastructure is powered by AWS, Vercel, and Google Cloud.

Do you work with companies in the United States?

Yes, we work with clients in over 5 countries including the United States, Bolivia, Chile, Peru, and Argentina. Our team is fully prepared to work remotely with constant communication, aligned with US time zones.

How much does a software development project cost?

Each project is unique and cost depends on scope, complexity, and required technologies. We offer free consultations where we evaluate your project and provide a detailed estimate. Contact us to schedule a meeting.

Do you offer post-launch maintenance and support?

Yes, we offer maintenance and post-launch support plans that include bug fixes, security updates, performance optimization, and new features. We ensure your product continues to work flawlessly.

What is nearshore software development?

Nearshore development means working with a team in a similar time zone. Based in Bolivia (GMT-4), we overlap with US business hours, enabling real-time collaboration at competitive rates without the communication challenges of offshore teams.

BORING

, but not that Boring

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CASE STUDY

ChildFund

Sector

AI Agents · Sponsorship process optimization · Americas Region (Confidential)

Client

ChildFund · Americas Region (Confidential · under NDA)

Chat-first platform with AI agents that replaces the most expensive manual outsourcing steps in ChildFund's sponsorship cycle. It performs proactive QA on correspondence and provides traceability for local partners, country offices and the international office, with projected annual savings of US$ 250,000.

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AI Agents✦Chat-first✦Correspondence QA✦Sponsorship✦NGO · Americas✦Confidential✦AI Agents✦Chat-first✦Correspondence QA✦Sponsorship✦NGO · Americas✦Confidential✦AI Agents✦Chat-first✦Correspondence QA✦Sponsorship✦NGO · Americas✦Confidential✦AI Agents✦Chat-first✦Correspondence QA✦Sponsorship✦NGO · Americas✦Confidential✦

About

Multi-agent AI system for ChildFund Americas that automates the child sponsorship cycle and replaces the most expensive outsourcing steps with an audited pipeline + human review. It runs 9 end-to-end flows (Enrollment, Unavailable, Welcome, Sponsor, Reply, Initiated, CPR, DFC and Disaffiliation), 18 AI skills and 6 roles, covering 5 countries with projected annual savings of US$ 250,000. Includes a Quality Gate for incoming F2 (Excel, CSV, Word, PDF or photo) with per-child score, batch QA and QC, a Savings vs outsourcing panel, SLA Cockpit and event-sourced audit. Internal product, private access under NDA.

Project brief

From complexity to a working product.

The challenge

ChildFund's sponsorship cycle moves millions of items a year (F2, letters, CPRs, DFCs) among local partner, country office and international office, with outsourcing charging for each processed item. The challenge was to replace the most expensive manual steps without losing traceability or data sovereignty, maintaining proactive QA over correspondence, safeguarding children's information and a clear operating model by role and country so each actor only sees what corresponds to them — all backed by a concrete business case that can be brought to the FY27 budget conversation.

The solution

We designed a chat-first platform with AI agents that models 9 end-to-end flows of the sponsorship cycle and connects them with 18 AI skills, 6 operational roles and 5 countries. The Quality Gate processes F2 in any format (Excel/CSV in batch, or Word/PDF/photo one-off) and issues a traffic light and score per child; batch QA and CPR QC review correspondence and reports; the Savings vs outsourcing panel counts real items from the event stream and multiplies them by the unit cost to show accumulated avoided cost, current month and annual projection. The architecture combines Next.js 15, React 19, Tailwind 4 and strict TypeScript on the frontend; Vercel AI SDK with Claude 4.7, Gemini 3 Pro and Whisper for the AI layer; InsForge (Postgres) with an event-sourced model on the backend; and full traceability for safeguarding and QA on the audit layer.

Platform

A tour of the system

Full model · 9 end-to-end flows and 6 roles, one place

View of the operating model: full sponsorship cycle in 9 flows (Enrollment, Unavailable, Welcome, Sponsor, Reply, Initiated, CPR, DFC, Disaffiliation) and 6 roles (Local partner, Outsourcing, Country office, Sponsorship officer, International office, Admin), where each actor only sees the modules they operate with their country or partner scope and handoff between roles. Technical stack built for data sovereignty and full audit: Next.js 15 + React 19 + Tailwind 4, Vercel AI SDK with Claude 4.7 and Gemini 3 Pro, Whisper, InsForge (Postgres) event-sourced and traceability for safeguarding and QA.

ChildFund authentication screen for outsourcing, country offices and local partners. Private access under NDA; each user enters the platform with their role and only sees the modules and data that correspond to them, with data sovereignty over children's information.

Quality Gate · AI that reads the F2 and returns a quality traffic light

Module where the partner uploads the F2 (Excel/CSV in batch or Word/PDF/photo one-off) and the system reads it, transcribes the data and returns a quality traffic light with score per child. The gate requests remain in history Pending / Completed / Rejected, with key fields (child, child number, created, moves to Unavailable, status, traffic light, score, monitoring) ready for audit. Per-partner reporting included in the module header.

Savings vs outsourcing · Live business case for FY27

Strategy panel · Business value that counts each item already processed (captures by the gate, letters and CPRs by batch QA) and multiplies it by the cost the outsourcing charges to process it. It shows accumulated avoided cost, this month and annual projection (run-rate) reading only the event log, without manual estimates — the number that backs the FY27 budget conversation with the international office.

Highlights

US$ 0K

Projected annual savings vs outsourcing

End-to-end flows of the sponsorship cycle

AI skills · 6 roles · 5 Americas countries

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Back

CASE STUDY

ChildFund

Sector

AI Agents · Sponsorship process optimization · Americas Region (Confidential)

Client

ChildFund · Americas Region (Confidential · under NDA)

Scroll to explore

About

Project brief

From complexity to a working product.

The challenge

The solution

Platform

A tour of the system

Full model · 9 end-to-end flows and 6 roles, one place

Quality Gate · AI that reads the F2 and returns a quality traffic light

Savings vs outsourcing · Live business case for FY27

Highlights

US$ 0K

Projected annual savings vs outsourcing

End-to-end flows of the sponsorship cycle

AI skills · 6 roles · 5 Americas countries

Back to all projects