
Built for Teams That Ship
Build intelligent, autonomous AI agents that think, plan, and execute complex tasks independently. Our AI agent development services create automation systems that adapt, learn, and scale.
Scope my AI agent build→Enterprise-grade security and compliance built into every engagement.
Nearshore teams that work U.S. hours — available for standups, reviews, and real-time collaboration.
Mid-career to senior engineers, hand-selected and tested before they ever join a client team.
From first call to first commit in 1–2 weeks. No long procurement cycles.
Consistently top-rated by verified clients across Clutch, DesignRush, and The Manifest.
Clients don't just renew — they grow with us. Annual growth in renewals reflects lasting partnerships.
AI agents are no longer a research curiosity — they're the architecture behind enterprise automation that actually holds up under production load. Autonomous agents plan, use tools, call APIs, and adapt mid-task without hand-holding, which means the engineering underneath them has to be airtight: robust state management, reliable tool orchestration, graceful failure handling, and the security boundaries that keep an autonomous system from becoming a liability.
Codieshub has been building production AI systems since before the current wave, which means our engineers understand what separates a compelling demo from a system your ops team can sleep through. We design agentic architectures that are observable, recoverable, and extensible — built on frameworks like LangGraph, AutoGen, and CrewAI where they fit, and custom orchestration layers where they don't.
Our LatAm engineering teams work U.S.-aligned hours, so iteration cycles stay tight and your internal stakeholders don't have to wait until morning for answers. Whether you're automating a document-intensive workflow, building a multi-agent research pipeline, or replacing a brittle RPA stack with something that can actually reason, we scope the work to match your readiness level and deliver incrementally.
Most AI agent projects stall at the prototype stage because the underlying architecture wasn't designed for the chaos of real data — malformed inputs, slow external APIs, ambiguous instructions, and edge cases the happy-path demo never touched. Teams end up with agents that work in demos but hallucinate, loop, or silently fail in production.
Codieshub architects agentic systems with production constraints baked in from the start: structured tool schemas, retry and fallback logic, human-in-the-loop checkpoints where the risk profile demands it, and observability instrumentation so you can trace every decision an agent makes. We build in stages — a single-agent proof of concept first, then expand to multi-agent topologies only when the simpler system has proven reliable.
Clients typically see measurable reduction in manual processing time within the first production release, with a system designed to expand its task scope as confidence grows. You get full ownership of the codebase, documented architecture, and engineers who can hand off cleanly to your team or stay on for ongoing iteration.
Tell us the workflow you want to automate — we'll respond with a realistic architecture and timeline.
The Work
Archive · 2016 → 2026
Browse all 35 cases→
Healthcare
Healthcare SaaS for mPATH Health
Paradigm Personality Labs
HR
HR SaaS for Paradigm Personality Labs
Levers Labs
Automation
AI/ML Automation Platform for Levers Labs
Percensys Core Learning
Education
Learner & Admin Workflows for Percensys
Kiwi
Logistics
AI & ML Powered Logistics for Kiwi
Rodeo
E-commerce
Shopify Subscription Plugin Built in 8 Weeks
Investment List
Fintech
Fintech Web Platform for Investor Discovery
Dot Drive
Fintech
Fintech Web Product for Dot Drive
TeamBuilder
Healthcare
Healthcare SaaS for TeamBuilder
4.9 / 5
Average client rating across platforms
93%
Net Promoter Score
150%
Client retention rate
SOC 2
Type II certified
Four ways to work with us — from surgical staff augmentation to fully managed delivery. All models share the same senior-first talent bench.
Full-time engineers embedded in your team for long-running engagements.
Explore Dedicated Teams↗Add senior specialists to an existing team — vetted, onboarded, and up to speed in weeks.
Explore Staff Augmentation↗Managed fixed-scope projects with a committed timeline and deliverables.
Explore Project Delivery↗Fractional senior technical leadership for architecture, hiring, and strategy.
Explore Virtual CTO↗Why Codieshub
The shortlist we get asked about on every call — what actually separates Codieshub from a dev shop.
We design agent topologies — hierarchical, mesh, or event-driven — matched to your workflow complexity, with clear delegation boundaries so agents don't conflict or duplicate work.
Agents need reliable tools. We build and harden the function schemas, API wrappers, and database connectors that let your agents interact with real systems without silent failures.
Every agent run is traced, logged, and surfaced in dashboards you can actually read. When something goes wrong, you know exactly which step, which tool call, and which input caused it.
Autonomous systems need hard limits. We implement input sanitization, output validation, permission scoping, and human escalation triggers to keep agents operating within safe boundaries.
We ship working agents incrementally — a single reliable agent before a complex swarm, validated against your real data at each step so you're never betting the project on a big-bang release.
Our LatAm teams overlap fully with U.S. business hours, so you get the async efficiency of nearshore without the timezone lag that kills momentum on fast-moving AI projects.
Reviews

Lisa Dunbar
CEO · Paradigm Labs
Paradigm Labs case study→“They did an excellent job balancing scientific nuance with a user-friendly experience. It's clear they care about both rigor and design.”

Vito Robles
COO · Percensys
Percensys case study→“They took feedback seriously, refined the details, and made sure our content and workflows were presented in a way that really works for our learners and admins.”

Oliver Dlouhy
CEO · Kiwi
Kiwi case study→“We move fast and deal with a lot of edge cases. They kept up without cutting corners, which is rare. The team stayed responsive across time zones.”

Ryan Pamplin
CEO · Blendjet
Blendjet case study→“Managing global scale requires extreme technical precision. Codieshub re-architected our funnels to perform under massive pressure.”

Steve Gebhardt
Founder · RSVLTS
RSVLTS case study→“Our old setup crashed during every major drop until Codieshub built a beast of an engine for us. They handled our traffic spikes perfectly.”

Farid Huseynov
CEO · Kapital Bank
Kapital Bank case study→“Reliability and scalability are critical for us. They approached the engagement with a strong technical foundation and a clear process.”

Michael Ou
Founder · CoolBitX
CoolBitX case study→“Security and precision are non-negotiable for us. They demonstrated solid technical judgment, were open to feedback from our engineers, and iterated quickly.”

John Bradford
CEO · PetScreening
PetScreening case study→“An external team can be just as committed and driven as our internal one. Their dedication and attention to detail have made them invaluable.”

Davis Rosser
CEO & Co-founder · Elite Amenity
Elite Amenity case study→“The digital concierge we co-built is more than tech — it's a paradigm shift in resident experience. Luxury brands can now offer faster services.”
Enterprise-grade security and compliance across every engagement.
Nearshore teams that overlap with your working hours for real-time collaboration.
Near-perfect satisfaction scores across Clutch, DesignRush, and Manifest.
Process
Our engineers are not freelancers, and we are not a marketplace. Dedicated Codieshub seniors, seated with your team.
Before kickoff
Pre-kickoff technical and strategic review.
Before a single line of code, we sit with your team to align on stack, constraints, and what success looks like. Our VP Eng, CTO, and senior leads join — not a sales engineer.
Full review of your stack, goals, and constraints before kickoff
Session led by VP Eng, CTO, and the senior leads who'll staff the work
Architecture, tooling, and team shape agreed before the first sprint
Questions
The questions we get on every intro call — answered without the marketing gloss.
A focused single-agent system handling a well-defined workflow — document extraction, email triage, API orchestration — typically reaches a production-ready v1 in 6 to 10 weeks. That includes scoping, architecture, tool integration, testing against real data, and a hardening pass. Multi-agent systems with complex orchestration run 12 to 20 weeks depending on the number of tools, the reliability requirements of each integration, and how much of the surrounding data pipeline we need to build or stabilize first.
Keep exploring