Artificial intelligence for business: from ideas to real-world applications.
AICore Labs builds production-ready agents, models and automations that fit the tools your team already uses — Slack, Notion, HubSpot, Salesforce, GitHub and 80+ more.
Our method:
the right questions first.
Understand, design, experiment, verify: the method we use to work out where AI can really be applied, and where a simple automation is enough.
Four steps. One clear goal.
We avoid complex solutions when a simple workflow can solve the problem.
- 01
Understand
Analyse the process, tools, information and desired outcome. In practice, this is the process assessment.
- 02
Design
Define the architecture, integrations and technical constraints.
- 03
Experiment
Build a prototype and observe how the system behaves.
- 04
Verify
Test, document the limitations and define improvements.
Building over time.
No shortcuts.
AICore Labs is an entrepreneurial project in development. Our skills are being consolidated through technical trials and by documenting our experiments.
- NowAutomations, API integrations and a demonstration CRM portfolio.
- ExploringAI agents, conversational systems and generative applications.
- Looking aheadRepeatable solutions, more structured services and possibly proprietary software products.
These items describe development directions, not achieved results or guaranteed commercial deadlines.
Let’s start from the real problem.
Share an operational challenge: in the assessment we evaluate whether and how it makes sense to automate it.
What we build for you.
Six areas, one stack. Composable or end-to-end, cloud or on-premise.
AI Agents
Autonomous agents handling tickets, leads, research and multi-step workflows end-to-end.
Process automation
Cross-tool automations that remove manual steps between CRM, email, knowledge base and ERP.
RAG & knowledge
Retrieval systems on proprietary data with grounding, citations and granular access control.
Custom models
Fine-tuning, distillation and on-prem deployment of models tailored to your domain.
AI analytics
Predictive dashboards that turn your data into daily operational recommendations.
AI dev tooling
Internal copilots, code-review agents and doc generation for engineering teams.
Our model family.
Four open and proprietary models, designed for real enterprise scenarios.
AICore-Atlas 70B
General reasoningMultilingual foundation model with chain-of-thought reasoning tuned for enterprise workflows.
AICore-Helix 8B
Edge / on-deviceCompact model running on-prem on a single consumer GPU. Ideal for high-confidentiality scenarios.
AICore-Mosaic Vision
MultimodalUnderstanding of images, PDFs and scanned documents with structured extraction up to 98.4% accuracy.
AICore-Pulse
EmbeddingsMultilingual embedding model, top-3 on the Italian and French MTEB benchmark.
Measurable outcomes, not demos.
CRM automation with n8n, Notion, AI and Brevo
A process that brings together a database, AI-assisted message drafting, three communication stages and record updates.
Catalog intelligence for DTC e-commerce
Automatic generation of descriptions, attributes and consistent imagery across 240k multi-language SKUs.
Clinical assistant for medical reporting
Transcription, ICD-10 coding and report generation grounded on the patient record.
Multilingual contract review agent
Comparative clause analysis, risk scoring and automatic redlining inside Microsoft Word.
Publications.
Helix: Efficient Inference for 8B-scale Mixture-of-Experts Models
We cut inference latency by 47% while preserving 99.2% of the base model performance.
Grounded Generation with Verifiable Citations at Scale
A framework for RAG generation with precise sentence-level attribution over corpora of millions of documents.
Mosaic-Vision: Document Understanding Beyond OCR
A unified architecture that beats traditional OCR+LLM systems on 11 document AI benchmarks.
Where we're heading.
An interactive map of our milestones. Full transparency on what's live, building and coming.
Atlas 70B public release
Open weights of the multilingual foundation model.
Agent Runtime v2
Parallel multi-agent execution with hierarchical planner.
AICore Studio
No-code IDE to build and version enterprise agents.
On-prem appliance
Certified hardware for air-gapped deployment.
Mosaic Vision Pro
Real-time video and document-stream understanding.
Global expansion
Offices opening in London, Singapore and New York.
AICore Safety Lab
Research center dedicated to alignment and red-teaming.
AICore-X foundation
New generation of models with native agentic reasoning.
We integrate every tool you already use.
80+ connectors out of the box. No process changes, just more speed.
Companies that already trust us.
Secure by design.
Security isn't a feature: it's the foundation of everything we ship.
End-to-end encryption
AES-256 at rest, TLS 1.3 in transit, customer-managed keys available.
Compliance
SOC 2 Type II, ISO 27001, GDPR, AI Act ready. HIPAA for healthcare.
Data residency
EU-only or on-premise deployment. No data leaves your perimeter.
Observability
Full audit log, prompt-level tracing and optional human-in-the-loop.
We build in the open.
Parallel sub-agent execution with hierarchical planner. Latency −31% on multi-step flows.
Atlas 70B: new checkpoint with +4.1 points on MMLU-Pro and native support for 16 languages.
Public beta of AICore Studio: visual builder and Git-style versioning for agents.
ISO 27001 certification achieved. Customer-managed keys available on all Enterprise plans.
Built for builders.
Living docs, runnable examples and SDKs in three languages.
Open full documentationFrom the lab.
Beyond chat: why AI agents are the new UI
How autonomous agents are replacing dashboards inside modern enterprises
RAG in production: 7 mistakes you'll pay for
Lessons learned deploying retrieval-augmented systems at enterprise scale
The AI Act is in force. Now what?
A practical guide for CTOs and compliance leads
Fine-tuning vs prompting: when it's actually worth it
A decision matrix based on 40+ enterprise projects
Evaluation harness: how we automated 1,200 agent tests
Behind the scenes of the QA system we use internally
On-prem GPU: the private data center reborn
When bringing AI in-house becomes cheaper than the cloud
Beyond chat: why AI agents are the new UI
How autonomous agents are replacing dashboards inside modern enterprises
RAG in production: 7 mistakes you'll pay for
Lessons learned deploying retrieval-augmented systems at enterprise scale
The AI Act is in force. Now what?
A practical guide for CTOs and compliance leads
Fine-tuning vs prompting: when it's actually worth it
A decision matrix based on 40+ enterprise projects
Evaluation harness: how we automated 1,200 agent tests
Behind the scenes of the QA system we use internally
On-prem GPU: the private data center reborn
When bringing AI in-house becomes cheaper than the cloud
Frequently asked questions.
Build with us.
A 4-week pilot. Zero risk, measurable impact.