Codieshub
code

Custom AI Agent Development Services

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
Why Codieshub

Built for Teams That Ship

verified

SOC 2 Certified

Enterprise-grade security and compliance built into every engagement.

schedule

Time-Zone Aligned

Nearshore teams that work U.S. hours — available for standups, reviews, and real-time collaboration.

groups

Vetted Senior Talent

Mid-career to senior engineers, hand-selected and tested before they ever join a client team.

speed

Fast Onboarding

From first call to first commit in 1–2 weeks. No long procurement cycles.

star

4.9 Clutch Rating

Consistently top-rated by verified clients across Clutch, DesignRush, and The Manifest.

trending_up

150% Retention Rate

Clients don't just renew — they grow with us. Annual growth in renewals reflects lasting partnerships.

Custom AI Agent Development Services

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.

The challenge

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.

Our approach

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.

The outcome

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.

Scope my AI agent build

Tell us the workflow you want to automate — we'll respond with a realistic architecture and timeline.

The Work

Shipped systems. Referenceable results.

Archive · 2016 → 2026

Browse all 35 cases
Featured · 01

Healthcare

mPATH Health

Healthcare SaaS for mPATH Health

Read the mPATH Health case
  1. Paradigm Personality Labs

  2. Levers Labs

  3. Percensys Core Learning

  4. Kiwi

  5. Rodeo

  6. Investment List

  7. Dot Drive

  8. TeamBuilder

Trusted Partner

The metrics that follow from shipping with senior engineers

4.9 / 5

Average client rating across platforms

93%

Net Promoter Score

150%

Client retention rate

SOC 2

Type II certified

Engagement Models

Pick the engagement that fits

Four ways to work with us — from surgical staff augmentation to fully managed delivery. All models share the same senior-first talent bench.

Why Codieshub

Six reasons teams stay past the pilot.

The shortlist we get asked about on every call — what actually separates Codieshub from a dev shop.

Reviews

Nine CEOs on reference. Three platforms verify the work.

  • Clutch 4.9
  • DesignRush 4.9
  • The Manifest 5.0
Lisa Dunbar

Lisa Dunbar

CEO · Paradigm Labs

“They did an excellent job balancing scientific nuance with a user-friendly experience. It's clear they care about both rigor and design.”

Paradigm Labs case study
Vito Robles

Vito Robles

COO · Percensys

“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.”

Percensys case study
Oliver Dlouhy

Oliver Dlouhy

CEO · Kiwi

“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.”

Kiwi case study
Ryan Pamplin

Ryan Pamplin

CEO · Blendjet

“Managing global scale requires extreme technical precision. Codieshub re-architected our funnels to perform under massive pressure.”

Blendjet case study
Steve Gebhardt

Steve Gebhardt

Founder · RSVLTS

“Our old setup crashed during every major drop until Codieshub built a beast of an engine for us. They handled our traffic spikes perfectly.”

RSVLTS case study
Farid Huseynov

Farid Huseynov

CEO · Kapital Bank

“Reliability and scalability are critical for us. They approached the engagement with a strong technical foundation and a clear process.”

Kapital Bank case study
Michael Ou

Michael Ou

Founder · CoolBitX

“Security and precision are non-negotiable for us. They demonstrated solid technical judgment, were open to feedback from our engineers, and iterated quickly.”

CoolBitX case study
John Bradford

John Bradford

CEO · PetScreening

“An external team can be just as committed and driven as our internal one. Their dedication and attention to detail have made them invaluable.”

PetScreening case study
Davis Rosser

Davis Rosser

CEO & Co-founder · Elite Amenity

“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.”

Elite Amenity case study

Why Teams Choose Us

verified

SOC 2 Certified

Enterprise-grade security and compliance across every engagement.

schedule

Time-Zone Aligned

Nearshore teams that overlap with your working hours for real-time collaboration.

workspace_premium

Top Rated

Near-perfect satisfaction scores across Clutch, DesignRush, and Manifest.

Process

How we deliver every sprint.

Our engineers are not freelancers, and we are not a marketplace. Dedicated Codieshub seniors, seated with your team.

Before kickoff

First-touch deep dive.

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.

  1. Full review of your stack, goals, and constraints before kickoff

  2. Session led by VP Eng, CTO, and the senior leads who'll staff the work

  3. Architecture, tooling, and team shape agreed before the first sprint

Questions

Frequently asked, honestly answered.

The questions we get on every intro call — answered without the marketing gloss.

  1. 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.

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