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How It Works

From request to deliverable — a five-step intelligent pipeline.

Pipeline

Five Steps to Outcomes

1
Understand

Parse the request and select the optimal strategy (Fast / ReAct / Swarm / Hybrid).

2
Plan

Break down into steps and choose tools — search, files, code, images, PPT.

3
Execute

Run actions in controlled environments — EEA-first routing, sandboxed code.

4
Verify

Critic/tester patterns or Swarm verification for accuracy and quality.

5
Deliver

Final output — report, SOP, deck, action plan — executive-ready.

Knowledge Layer

RAG — Retrieval-Augmented Generation

RAG allows Obsigen to answer using your knowledge, reducing hallucinations and improving traceability. Every answer can cite the source document, section, and version.

Recommended RAG Pipeline
  1. Ingest: SOPs, policies, ERP docs, tickets, product catalogs
  2. Process: Parse → chunk → metadata enrichment (dept, ACL, version, date)
  3. Embed: Semantic vectors for fast similarity retrieval
  4. Store: EU-hosted vector DB + metadata index
  5. Retrieve: Top-k + filters (ACL, recency, system context)
  6. Generate: Grounded response + evidence snippets
RAG Source Example Content Business Outcome
ERP / MRP BOMs, routings, stock, lead times Faster planning, fewer stockouts
SOC KB Runbooks, detections, incident history Faster triage and response
CRM / E-commerce Product info, pricing, segmentation Better next-best actions
SOP / ISO docs Procedures, audits, compliance Consistency + audit evidence
Customization

Trainable AI — Fine-Tuning

Fine-tuning adapts Obsigen to your terminology, tone, and process patterns. Teams get answers that match how your business actually works.

EU-Safe Training Posture
  • Train on approved datasets only
  • Keep training data & artifacts in EEA storage
  • Add evaluation gates and red-team prompts before deployment
Method Best For Notes
SFT / Instruction Tuning Consistent "house style" answers Needs curated examples
LoRA Adapters Cost-effective specialization Per-tenant or per-team variants
Preference Tuning Align to internal standards Uses ranked outputs
Tool-Use Tuning Better planning/execution Improves agent reliability
Technical Stack

Reference Implementation

LayerTechnology
Backend APISymfony 7, PHP 8.2 — REST + SSE streaming
FrontendSymfony + Vanilla JS — streaming UI
DatabaseMySQL 8.0 — chats, users, sessions
Cache / Rate LimitsRedis 6+ — throttling, TTL storage
AuthJWT (HS256) — secure sessions
ServiceTechnology
Search (self-hosted)SearXNG (Docker) — private meta-search
Search (premium)Brave Search API Pro
SandboxDocker + Python 3.11 — isolated execution
AI InferenceOpenAI-compatible API via EU provider
Images / VisionFLUX.1-schnell / Llama-4-Scout-17B

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