NAscii-Core
AI Agents

AI Agent Development Services

Autonomous AI agents that handle customer conversations, sales, internal tasks and document work — reliably and at scale.

Based in Casablanca, Ascii-Core delivers AI agent development services to companies across Europe, the GCC and North Africa — building autonomous systems that reduce support costs and accelerate operations.

75%
fewer support tickets
67%
reduction in manual hours
80%
faster employee onboarding

Key Takeaways

  • AI agents are autonomous software systems that use large language models to plan, decide and take actions across multiple tools and data sources without constant human direction.
  • Agents connect to CRMs, helpdesks, databases and APIs to complete multi-step tasks — including querying, updating records, sending messages and triggering workflows.
  • Production agents are built on orchestration frameworks such as LangGraph and MCP, with tool calling, memory and human-in-the-loop approval for sensitive actions.
  • A single AI agent commonly resolves 70–75% of routine customer queries, cutting response time from hours to seconds.
  • Ascii-Core deploys production AI agents for companies across Morocco, Europe, the UAE and Saudi Arabia.
Overview

What is AI Agents?

AI agents are autonomous software systems that use large language models to plan, decide and take actions across multiple tools and data sources — without constant human direction. Unlike basic chatbots, agents can query databases, update CRMs, send emails, trigger workflows and escalate intelligently, completing multi-step tasks end to end.

Ascii-Core builds custom AI agents for businesses across Europe, North Africa and the GCC — from customer support agents that resolve 75% of tickets automatically to internal assistants that give every team instant access to company knowledge.

The Problem

What holds companies back

We've seen these challenges across dozens of engagements. They're fixable.

  • Repetitive tasks that never get automated
  • Support teams overwhelmed by routine questions
  • Knowledge trapped in the heads of a few people
  • Hours lost to manual document handling
What We Build

What we build

Production-grade ai agents solutions designed around your specific context.

Customer Agents

Resolve support and sales conversations end to end.

Sales Agents

Qualify, follow up and book meetings automatically.

Internal Assistants

Give every team an expert on call 24/7.

HR Assistants

Answer policy questions and streamline onboarding.

Knowledge Assistants

Instant answers grounded in your documentation.

Document Assistants

Extract, summarise and act on documents at scale.

Use Cases

Use cases and outcomes

Real scenarios where we've delivered measurable results.

Customer Support Agent

An AI agent that handles tier-1 support queries end-to-end, pulling from a knowledge base and escalating edge cases to humans.

75% fewer tickets

Sales Qualification Agent

Engages inbound leads, asks qualifying questions and books discovery calls in the calendar automatically.

3× faster lead response

Internal HR Assistant

Answers employee questions about policies, benefits and onboarding from company documents — available 24/7.

80% faster onboarding

Document Processing Agent

Extracts structured data from contracts, invoices and forms, validates it and routes it to the right system.

67% reduction in manual hours

E-commerce Support Agent

Handles order status, returns and product questions across chat channels with no human involvement for standard queries.

70% auto-resolved queries
75%
fewer support tickets
67%
reduction in manual hours
80%
faster employee onboarding
Implementation Timeline

From kickoff to live system

A typical engagement runs 6–8 weeks. Here is what happens each week so you always know where things stand.

  1. Week 1

    Discovery & Process Mapping

    We map your goals, constraints and existing systems to define a clear, measurable scope.

  2. Week 2

    Architecture & Integrations

    We design the technical blueprint — data flows, models, integrations and security controls.

  3. Weeks 3–5

    Development

    We build in tight iterations with weekly demos so you see progress every step of the way.

  4. Week 6

    Deployment

    We ship to production with monitoring, documentation and a smooth handover.

  5. Week 7+

    Optimisation

    We monitor, tune and evolve the system as usage patterns emerge and needs grow.

Technology

Tools we use

We choose proven, production-tested technologies — not whatever is trending.

OpenAIClaudeLangGraphMCPVector DBsn8n
AI AgentsAgentic AILLM AgentsAutonomous AILangGraphMCPAI AutomationEnterprise AI Agents
Case Studies

Results from similar projects

Real outcomes from clients with the same challenges you're facing.

Why Ascii-Core

Why choose Ascii-Core for ai agents?

There are many agencies offering ai agents services. Here is what makes Ascii-Core the right engineering partner for companies that need production systems — not prototypes.

20+ projects delivered
5+ countries served
Q1 avg. payback
  • Agents are built with tool calling, memory and conditional branching — not scripted decision trees.
  • Weekly engineering demos show the agent working in your environment before it goes live.
  • Clients commonly automate 70–75% of routine queries, reducing support headcount requirements.
  • Human-in-the-loop approval for sensitive actions is standard — not an optional add-on.
  • Ongoing optimisation and retraining support available after deployment to improve coverage over time.
Explore

Related services

Industries

Industries we serve

Compare

Tool comparisons

Not sure which approach is right? Read our unbiased comparisons related to ai agents.

FAQ

Common questions

Everything you need to know about our ai agents services.

Design your first AI agent

Book a short call and we'll show you exactly how we'd approach your situation.

Reviewed by the Ascii-Core Engineering Team — specialists in AI engineering, workflow automation, product development and enterprise software architecture. Content reviewed regularly to reflect current technologies and implementation practices. · Updated June 2026