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AI Agent & Copilot Development Services

AI Agent & Copilot Development

Quecko builds AI agents and copilot systems that go far beyond chat interfaces. We engineer autonomous agents that reason through multi-step tasks, call external tools, make decisions under uncertainty, and execute real workflows — embedded directly into your product, your operations, or your users' hands.

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400+clients across 20+ countries
$300M+in funds generated
250+products built
150+engineers worldwide
400+clients across 20+ countries
$300M+in funds generated
250+products built
150+engineers worldwide
400+clients across 20+ countries
$300M+in funds generated
250+products built
150+engineers worldwide
400+clients across 20+ countries
$300M+in funds generated
250+products built
150+engineers worldwide
What We Build

Comprehensive AI Agent Engineering

01

Autonomous Task Agents

Multi-step agents that break complex goals into sub-tasks, select and call the right tools, handle errors, and deliver results — without human intervention. We build agents for data analysis, research, code generation, operations automation, and domain-specific workflows.

02

Product Copilots & Assistants

In-product AI assistants that help users navigate complex workflows, generate content, analyze data, and make decisions. We integrate copilots with your existing UI, data models, and business logic — not generic chat overlays.

03

Tool-Calling & API Orchestration

Agent architectures with structured function calling — database queries, API integrations, file operations, web scraping, and third-party service orchestration. We build reliable tool interfaces with validation, retry logic, and error handling.

04

Multi-Agent Systems

Collaborative agent architectures where specialized agents coordinate on complex tasks — a planner agent, a researcher agent, a coder agent, and a reviewer agent working in concert with defined handoff protocols.

05

Memory & Context Management

Long-term memory systems (vector stores, knowledge graphs), session context tracking, and retrieval-augmented generation (RAG) pipelines. We build agents that learn from interactions and maintain coherent context across sessions.

06

Guardrails & Safety Systems

Output validation, action confirmation gates, content filtering, hallucination detection, and cost controls. We build safety layers that prevent agents from taking catastrophic actions or generating harmful outputs.

The Challenge

Everyone's building "AI agents." Almost none of them work reliably in production.

The gap between a demo AI agent and a production AI agent is enormous. Demo agents hallucinate, loop infinitely, call the wrong tools, and crash on edge cases that real users hit in the first five minutes. Production agents need structured reasoning frameworks, reliable tool orchestration, graceful failure handling, memory management, and guardrails that prevent catastrophic actions — none of which come out of the box from wrapping an LLM API. Quecko builds agent systems with the engineering discipline of traditional software — tested, monitored, and hardened for real-world deployment where failures have real consequences.

Execution Blueprint

From Day 1 to Day 90: What AI Agent Execution Looks Like

01Day 1–15

Architecture & Prototyping

Use case mapping, LLM selection, reasoning framework design, tool interface specification, and rapid prototype for validation.

02Day 16–45

Core Agent Development

Agent logic implementation, tool integrations, memory/RAG pipeline, prompt engineering, and integration with product APIs and data sources.

03Day 46–75

Evaluation & Hardening

Systematic eval suite, edge case testing, hallucination mitigation, latency optimization, guardrail implementation, and cost profiling.

04Day 76–90

Production & Monitoring

Production deployment, observability setup, user onboarding, usage analytics, feedback loops, and continuous optimization.

Technology

Technologies We Master

Tools, frameworks, and protocols we use to build secure and scalable solutions.

LLM Providers

OpenAI (GPT-4o, o1)OpenAI (GPT-4o, o1)
Anthropic (Claude)Anthropic (Claude)
Google (Gemini)Google (Gemini)
MistralMistral
Llama (self-hosted)Llama (self-hosted)

Agent Frameworks

LangChainLangChain
LangGraphLangGraph
CrewAICrewAI
AutoGenAutoGen
custom agent architecturescustom agent architectures

Memory & RAG

PineconePinecone
WeaviateWeaviate
QdrantQdrant
ChromaDBChromaDB
pgvectorpgvector
knowledge graphsknowledge graphs

Observability

LangSmithLangSmith
LangFuseLangFuse
HeliconeHelicone
custom dashboardscustom dashboards

Infrastructure

PythonPython
FastAPIFastAPI
Node.jsNode.js
DockerDocker
KubernetesKubernetes
AWS/GCPAWS/GCP

Guardrails

NeMo GuardrailsNeMo Guardrails
Guardrails AIGuardrails AI
custom validation layerscustom validation layers
Our Edge

We Build Agents That Survive Contact With Real Users.

Our agents are tested against systematic evaluation suites, not just cherry-picked demos. We engineer for the edge cases that real users hit.

Production Engineering, Not Demo Engineering

Our agents are tested against systematic evaluation suites, not just cherry-picked demos. We engineer for the edge cases that real users hit.

Reliable Tool Orchestration

We build structured tool-calling interfaces with validation, retry logic, and error handling — not fragile string-parsing that breaks on unexpected inputs.

Full-Stack Integration

Our agents plug into your existing product — databases, APIs, UI components, and business logic — not standalone chatbot widgets.

250+ Products Shipped

We apply the same engineering discipline to AI agents that we bring to enterprise software, blockchain infrastructure, and mobile apps.

Our Work

Our Projects

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Social Proof

“The work Quecko has done has been absolutely brilliant. Extremely responsive, reliable, and fast — we can throw last minute requests in and they'll get them done by the end of the day.”

Tom Blears

Chief Executive Officer, Bitcast
Engagement

How We Collaborate

Dedicated AI Pod

Full-time AI engineers, ML engineers, and backend developers working as your agent development team.

Project-Based Agent Build

End-to-end agent development from architecture to production deployment, with evaluation and monitoring included.

AI Architecture Advisory

Standalone engagement for agent architecture review, LLM selection, or evaluation framework design.

FAQ

Frequently Asked Questions

A chatbot responds to user messages within a conversation. An AI agent autonomously executes multi-step tasks — calling tools, querying databases, making decisions, and delivering results — often without human prompting at each step. We build both, but agents are our specialty.

We select the optimal LLM for each use case — OpenAI GPT-4o/o1, Anthropic Claude, Google Gemini, Mistral, or self-hosted open-source models (Llama). We often use different models for different agent components based on cost, latency, and capability requirements.

We implement multi-layered guardrails: structured output validation, action confirmation gates, hallucination detection, content filtering, and human-in-the-loop escalation paths. Every agent deployment includes monitoring and alerting for anomalous behavior.

Yes. We specialize in embedding agents into existing SaaS products, enterprise platforms, and mobile apps — connecting them to your databases, APIs, and UI components rather than deploying standalone chat windows.

Blogs

Latest Stories from Quecko

Ready to build an AI agent that actually works in production?

From autonomous task agents and product copilots to multi-agent systems — Quecko builds AI that reasons, executes, and delivers results your users and operations can rely on.

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