Enterprise Agentic AI
AI agents that execute real work in your operations.
"Agents that classify, analyze, generate and search: integrated into your systems, with your data, in production."
6 weeks
from discovery to production
≈€120K
annual savings · per automated process · 3 FTE freed
Enterprise trust
The solution: agents that execute, not just assist.
Platform-agnostic. Integrated with your stack. In production in weeks.
At AyGLOO we build generative AI agents that integrate directly into your operations. Automated processes that read, classify, analyze and generate outputs in enterprise format, connected to your real systems.
Explainable AI in LLMs
- AyGLOO methods such as Chain-of-Thought and Graph-of-Thought enable analysis of model reasoning.
- Identification of prompt elements that influence the generated response.
- Hallucination detection through fact-checking and uncertainty metrics.
Enterprise integration
- CRM (Salesforce, HubSpot), ERP (SAP, Oracle), Email (Outlook, Gmail)
- Cloud storage, REST APIs, Webhooks, SFTP
- Without changing your current tech stack
Model-agnostic
- Claude (Anthropic) · GPT-4/5 (OpenAI) · Gemini (Google) · Llama (Meta)
- We choose the best model for each task
- Automatic updates in 24h when new versions appear
Security & compliance
- GDPR compliant · Data hosted in EU (Google Cloud / Azure)
- End-to-end encryption · Complete audit logs
- On-premise available per case
Team with certified experience in technologies such as Google Cloud · Microsoft Azure · Anthropic (Claude), among others.
How it works
From discovery to production in 6 weeks. No permanent consultants. No endless committees.
Discovery
1-day intensive session with your team. We identify the process, define inputs/outputs and success criteria.
- Analysis of the process to automate
- Sample of 20–50 real documents
- Technical proposal + ROI estimate in 72h
Pilot
We build the agent with your real data. Real-time metrics dashboard. We iterate based on feedback.
- Functional agent in 2 weeks
- Training with real cases
- Your team dedicates ~2h/week
Production
Full integration with your systems. Exhaustive testing, 24/7 monitoring and handover to the team.
- API / Email / Cloud integration
- Complete technical documentation
- Continuous support + updates included
Real cases. Real metrics.
Companies that stopped waiting and started executing.
Intelligent search: Bidafarma
150-agent call center spent 40% of time searching for products. Agent with access to 50,000+ pharmaceutical product catalog.
- → Search by active ingredient, symptom or brand
- → Integration: data scraping + Elasticsearch
- → Technology: GPT-4o + Elasticsearch
Email classifier: INWIT
1,200 emails/week classified and forwarded manually. Agent trained with internal area nomenclature.
- → Automatic classification with 96% accuracy
- → Intelligent routing by urgency and content
- → Technology: GPT-4o + Microsoft SSO
Tender assistant: ACEA
Evaluating technical criteria of tenders with 5 suppliers took 2 full days per analyst.
- → Reads proposals in Word, PDF and Excel automatically
- → Generates comparison in customized Word format
- → Technology: Gemini 2.0 Flash + Claude Sonnet 4.5
Product snapshot
Real examples of two cases in production: real inputs, actionable outputs, complete traceability.
Email triage and classification INWIT — agent in action
Each email —including its attached legal and contractual documents— is analyzed, classified, prioritized and routed automatically with explanation of the criteria applied.
Before the agent
3 people to read, categorize and forward emails, with complex attachments requiring full reading.
Improvements with the agent
- Classification and routing in seconds, without human intervention
- Automatic reading of attachments (PDF, Word, contracts)
- 96% precision in multi-criteria classification
- 3 FTE freed (~€120K/year)
- Complete traceability and audit logs for each decision
Live demo
Intelligent search Bidafarma — agent in action
The agent searches the complete catalog of 50,000+ products and returns contextualized results in seconds, with stock and clinical information included.
Before the agent
150 agents spent an average of 15 minutes per call searching for products in various catalogs, with dispersed information and lost calls during peak hours.
Improvements with the agent
- Average call time reduced from 15 to 10 minutes
- Capacity per agent: 4 to 6 calls/hour (+50%)
- Significant reduction in lost calls during peak hours
- Immediate access to specialized catalogs with stock included
- Answers to complex questions about characteristics in seconds
Live demo
Does your operations have processes that repeat every day?
Tell us about the process. In one discovery day we identify whether an AI agent can solve it, how, and with what return.