7 Phases. From mapping to production.

A proven framework that starts with understanding your context and ends with a Private AI system in production. Every phase has measurable outputs and concrete deliverables.

00

Discovery & Assessment

Before writing a single line of code, we map your context. We audit the data sources you already have, interview the people who will use the system, assess the team's digital maturity and catalog external sources relevant to your domain.

Data source auditKey user interviewsDigital maturityExternal source scan

Output: Data Map + Opportunity Matrix

01

Data Collection & Primary Sources

Set up the data collection infrastructure. We configure the OSINT engine, activate crawlers on industry sources, ingest internal data and configure change detection.

OSINT engine setupIndustry source crawlersInternal data ingestionMulti-format parsingChange detection

Output: Structured Data Lake

02

Gold Standard Construction

We build the quality baseline: curated gold documents, annotated and validated. We define the domain ontology and the benchmarks to measure answer quality.

Gold document selectionSupervised annotationDomain ontologyQ&A benchmarkQuality metrics

Output: Gold Standard + Benchmark + Ontology

03

Knowledge Graph & RAG Build

We deploy the RAG pipeline, build the Knowledge Graph, configure hybrid search and activate the Explorer. The system starts answering questions.

RAG pipeline deployKG buildHybrid search configExplorer setupThematic collections

Output: Operational Knowledge Base

04

Model Tuning & AI Agents

We select and calibrate AI models on the specific domain. We design specialized agents, configure tool use and validate performance against benchmarks.

Model selectionFine-tuning/LoRAAgent designTool use configBenchmark validation

Output: Calibrated AI Agents

05

Integration & Deploy

On-premise or private cloud deploy. We integrate with the existing ERP/CRM, customize the interface, configure RBAC and audit trail. We train the team.

On-premise deployERP/CRM integrationCustom UIRBAC & auditUser training

Output: System in production

06

Continuous Improvement

The system improves over time. We gather feedback, update the knowledge base, add new collections, re-tune the model and produce monthly reports.

Feedback loopKnowledge updateNew collectionsModel re-tuningMonthly reports

Output: AI that improves over time

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