AI Solutions for Startups & Funded Companies

You just closed your round. The board wants to see product velocity. Your two-person engineering team is already stretched thin. You need to ship an AI feature your investors are asking about, build the mobile app you promised in the pitch deck, and fix the scaling issues that showed up when you hit 10,000 users.

Hiring in the US means $180K-$250K per senior engineer, 3-month ramp-up, and the risk they leave in 8 months. That burns runway fast.

We’ve been the engineering partner for startups since 2014. KanbanZone — a project management SaaS with 50,000 users — was built with us. Metabeta, an investment platform connecting startups with investors, was built with us. vPeer, a social platform, was built with us. We know what funded companies need: speed, quality, and cost efficiency that extends your runway.

Your $200K US engineering budget becomes $60K-$70K with Contrive. Same quality. Same technology. Three times the runway.

Why Do Funded Startups Work with Contrive?

Because the math changes everything. When you’re burning $150K/month and have 18 months of runway, every dollar you save on engineering without sacrificing quality adds weeks to your survival window. And in startups, those extra weeks are often the difference between finding product-market fit and running out of cash.

Here’s what we bring to the table:

60-70% Cost Savings That Actually Work

This isn’t a bait-and-switch where you save money upfront and spend double fixing quality issues later. We have 66 professionals in our Lahore headquarters, including 20+ AI/ML engineers. Our team has built 250+ projects across web, mobile, AI, and SaaS. 95% of our clients come back for more work. That retention rate tells you more than any sales pitch.

A senior full-stack engineer in the US costs $180K-$250K/year loaded. With us, you get a dedicated senior engineer for a fraction of that. Scale to a team of 5 — backend, frontend, AI, mobile, QA — and you’re still spending less than two US hires.

Concrete example: One of our startup clients had a $600K annual engineering budget. They were considering hiring 3 engineers in San Francisco. Instead, they engaged a dedicated Contrive team of 7 (2 backend, 2 frontend, 1 AI/ML, 1 mobile, 1 QA) for $420K. They got more than double the output at 30% less cost.

Dedicated Teams, Not Freelancer Roulette

When you engage Contrive, you get a named team assigned to your project. They attend your standups. They’re in your Slack. They use your Jira. They understand your codebase, your architecture decisions, your product roadmap.

This isn’t a ticket-based outsourcing shop where you submit requirements and hope for the best. Your Contrive team operates as an extension of your engineering org. Same workflows, same tools, same accountability.

Build Across Web, Mobile, AI, and SaaS Simultaneously

Most startups need multiple things at once. The web app. The mobile app. The AI features. The infrastructure. With a US-based team, you’re either hiring specialists for each (expensive) or asking generalists to context-switch (slow).

Our team covers the full stack:

  • AI/ML: LangChain, CrewAI, AutoGen, LangGraph, custom agent architectures, voice AI
  • Backend: Python (FastAPI, Django), Laravel, Node.js
  • Frontend: React, Vue.js, Next.js
  • Mobile: React Native, Flutter
  • Infrastructure: AWS, GCP, Docker, Kubernetes
  • Data: PostgreSQL, MongoDB, Redis, Elasticsearch

One partner. One relationship. Everything your startup needs to build and ship.

Let’s talk about your startup’s engineering needs. We’ll scope it in 48 hours.

What AI Features Can We Build for Your Startup?

AI isn’t optional anymore. Your investors expect it. Your users expect it. Your competitors already have it. But building AI features right — in a way that actually works and scales — requires engineers who’ve done it before.

Our 20+ AI/ML engineers build AI agents, voice agents, and intelligent automation for startups across every vertical.

AI Agents That Do Real Work

Not chatbots that regurgitate FAQ answers. We build AI agents that take autonomous actions in your product:

  • Customer support agents that resolve tickets, process refunds, update accounts, and escalate intelligently
  • Data analysis agents that pull from multiple sources, generate reports, and surface insights for your users
  • Workflow automation agents that handle onboarding sequences, compliance checks, content moderation, and internal operations
  • Sales agents that qualify leads, draft proposals, schedule meetings, and update your CRM

These agents use LangChain, CrewAI, or AutoGen depending on the complexity. They connect to your existing APIs, databases, and third-party tools. They run autonomously within guardrails you define.

Voice Agents for Customer-Facing Operations

We built our own voice agent platform at voice.agent.contrivesol.com. For startups, voice agents solve a specific problem: you can’t afford a 15-person support team, but your customers expect to reach a human.

Voice agents for support handle inbound calls with natural conversation. They answer questions, troubleshoot issues, process requests, and escalate to your small human team only when necessary. Voice agents for sales qualify inbound leads, book demos, and follow up with prospects who went cold.

For a startup spending $20K/month on a 4-person support team, a voice agent reduces that to $5K-$8K/month while handling 3x the call volume.

Scalable Architecture from Day One

We’ve seen startups build fast, hit traction, then spend 6 months rewriting everything because the architecture couldn’t handle scale. We design for scale from the start without over-engineering.

That means:

  • Microservices where they make sense, monolith where they don’t (we’re pragmatic, not dogmatic)
  • Proper queue systems for async workloads
  • Database indexing and query optimization before you hit performance walls
  • CI/CD pipelines that let you ship multiple times a day
  • Monitoring and alerting so you know about problems before your users do

Startups We’ve Built With

KanbanZone — Project Management SaaS (50,000 Users)

KanbanZone is a visual project management platform built on Kanban methodology. We built the core application, scaled it to 50,000 active users, and continue to support its development. The platform handles real-time collaboration, workflow automation, and analytics — the kind of features that break if the architecture isn’t right.

Metabeta — Investment Platform

Metabeta connects startups with investors. We built the matching algorithms, the deal flow management system, and the communication infrastructure. This is a platform where data integrity and user experience both matter enormously — investors don’t tolerate bugs.

vPeer — Social Platform

vPeer is a social platform we built from the ground up. User profiles, content feeds, messaging, notifications, moderation — the full social stack. We handled the complexity of real-time features at scale and the content moderation challenges that every social platform faces.

Skolaro — Education Platform (1.5M+ Users)

Skolaro is a school management system serving over 1.5 million users. We built and scaled a platform that handles student records, attendance, grading, parent communication, and administrative workflows. When your platform serves 1.5 million people, reliability isn’t negotiable.

Grundsteuer Digital — Property Tax SaaS (Germany)

A SaaS product for German property tax compliance. We built it to handle the specific regulatory requirements of the German market, including multi-language support and compliance with local tax laws. This project demonstrates our ability to build for regulated industries in international markets.

See what we can build for your startup. Schedule a technical discovery call.

How Does the Engagement Model Work?

We’ve refined our process over 250+ projects. Here’s what working with us looks like:

Week 1: Technical Discovery

We spend the first week understanding your product, your architecture (or planned architecture), your team structure, and your priorities. This isn’t a sales exercise — it’s a technical deep-dive led by a senior engineer who will actually work on your project.

By the end of week one, you get:

  • A technical architecture document
  • A prioritized backlog with effort estimates
  • A team composition recommendation
  • A timeline with milestones

Weeks 2+: Sprint-Based Delivery

We work in 2-week sprints with demos at the end of each sprint. You see working software every two weeks. You provide feedback. We adjust. This continues until the product is shipped.

Your dedicated team joins your daily standups (we overlap with US time zones — our engineers work flexible hours to accommodate EST, CST, and PST). They’re in your Slack, your Jira, your GitHub. The communication overhead is minimal because they’re embedded in your workflow.

Ongoing: Scale Up or Down

Startup needs change fast. You might need 3 engineers this month and 7 next month when you’re pushing for a launch. Then back to 4 for maintenance mode. Our model flexes with you. No long-term contracts. No termination fees. Scale your team size based on what the product needs right now.

What About IP and Code Ownership?

You own everything. Every line of code, every design file, every deployment script, every piece of documentation. It’s in the contract. When the engagement ends, you have your complete codebase in your repository, fully documented, ready for any team to pick up.

We don’t hold code hostage. We don’t use proprietary frameworks that lock you in. We build with standard, widely-adopted technologies that any competent engineer can maintain.

The Runway Math

Let’s make this concrete.

Scenario: Series A startup, $3M raised, 18-month runway at current burn.

Option A: US Hiring

  • 3 senior engineers at $200K loaded = $600K/year
  • 1 AI/ML engineer at $250K loaded = $250K/year
  • 1 DevOps at $180K loaded = $180K/year
  • Total: $1.03M/year for 5 people
  • Runway impact: burns through engineering budget in ~14 months

Option B: Contrive Dedicated Team

  • 3 senior engineers = ~$180K/year
  • 2 AI/ML engineers = ~$140K/year
  • 1 DevOps = ~$50K/year
  • 1 QA engineer = ~$45K/year
  • 1 Project manager = ~$40K/year
  • Total: ~$455K/year for 8 people
  • Runway impact: 60% more engineering output at 56% less cost

With Option B, you get 8 people instead of 5, save $575K in year one, and extend your runway by months. That’s the difference between running out of money before Series B and having the metrics to close it.

4.7/5 on Clutch. 4.9/5 on Indeed. 95% client retention. 98% on-time delivery. These numbers exist because we’ve earned them across 250+ projects over 12 years.

Get a custom team proposal for your startup. 48-hour turnaround.

Frequently Asked Questions

How is Contrive different from other offshore development shops?

Three things. First, we’ve been doing this since 2014 — 12 years and 250+ projects. We’re not a body shop that spun up last year. Second, we have 20+ dedicated AI/ML engineers, which means your AI features are built by specialists, not generalists reading documentation for the first time. Third, our dedicated team model means your engineers are assigned to you, attend your standups, and build institutional knowledge about your product. Our 95% client retention rate reflects this — companies stay because the model works.

What if we already have an engineering team and just need to augment it?

That’s our most common startup engagement. Your CTO sets the architecture and priorities. Our team plugs into your existing workflows — same repo, same CI/CD, same code review process. We’ve done this with teams ranging from 2 founders to 30-person engineering orgs. The key is the first week of technical discovery where we align on standards, conventions, and communication patterns.

Can you build an MVP from scratch, or do you only augment existing teams?

Both. About 40% of our startup engagements start from scratch — founder has a vision, maybe some wireframes, and needs a team to build it. We handle architecture design, technology selection, development, QA, and deployment. KanbanZone and vPeer both started this way. The other 60% are augmentation or feature-build engagements with existing products.

How do you handle time zone differences?

Our headquarters is in Lahore, Pakistan (PKT, UTC+5). That gives us solid overlap with European time zones and workable overlap with US time zones. Our engineers work flexible schedules — for US clients, teams typically work 11 AM to 8 PM PKT, which covers 1 AM to 10 AM EST or 10 PM to 7 AM PST. We also have a US office in Danville, California for local coordination. Daily standups, Slack communication, and sprint demos all happen during your business hours.

What happens if we get acquired or need to transition to an internal team?

We’ve supported multiple transitions. Our code is clean, documented, and built on standard frameworks. During transition, we do knowledge transfer sessions with your incoming team, walk them through the architecture, explain the decisions we made and why, and support them through a handoff period. The goal is zero disruption. You own the code, you own the documentation, and we make sure whoever comes next can hit the ground running.