SHEET 01How It WorksARCHITECTURE

Architecture built for governed enterprise execution

assistents.ai combines four layers so data ingestion, reasoning, action, and governance remain explicit, testable, and auditable.

Talk to an Architect Platform Summary
  • Data Layer
  • Intelligence Layer
  • Execution Layer
  • Governance Layer
4Architecture layers, independently evaluable
300+Source systems across structured and unstructured
L5Intelligence maturity at agentic execution
100%Actions traceable through the audit chain
SHEET 02Architecture OverviewSTACK

From ingestion to governed action

The stack is designed so each layer can be evaluated independently while participating in one deterministic execution pipeline.

Layer responsibilitiesActive
RefLayerPrimary responsibility
L1Data LayerIngest, normalize, and correlate structured and unstructured context
L2Intelligence LayerApply deterministic grounding and rule-aware reasoning
L3Execution LayerRoute and execute actions with autonomy and approval controls
L4Governance LayerAudit, monitor, authorize, and report compliance evidence

4 layers · one deterministic pipeline

L1Data LayerL2Intelligence LayerL3Execution LayerL4Governance Layer
SHEET 03Layer ExplorerLYR-01..04

Inspect each architecture layer in detail

Each layer lists its responsibilities, controls, and execution impact. Read the stack top to bottom: context, reasoning, action, governance.

LYR-01INGEST

Layer 1 — Data Layer

Ingests and correlates structured systems and unstructured content into a unified context foundation.

LYR-01.01

Connectors (Structured Sources)

Schema discovery, incremental sync, and secured ingestion from ERP, CRM, HRIS, service, and infra systems.

LYR-01.02

Document Processors (Unstructured Content)

Format normalization, structural decomposition, semantic extraction, and embedding generation for documents.

LYR-01.03

Entity Resolution

Deterministic and probabilistic matching unify entity references across systems and content types.

LYR-01.04

Semantic Correlation Engine

Maintains relationships between entities, events, documents, and transactions for cross-source reasoning.

LYR-02GROUND

Layer 2 — Intelligence Layer

Applies deterministic grounding and business rules to produce traceable answers and recommendations.

LYR-02.01

Unified Context Engine (Entity Graph)

Assembles relevant context subgraphs per request and tracks evolving entity state.

LYR-02.02

Semantic Governor (Business Rules)

Encodes policy, threshold, temporal, and conditional business rules in machine-evaluable form.

LYR-02.03

Query Processor (Deterministic Grounding)

Transforms natural language into deterministic data retrieval and validates source-grounded responses.

LYR-02.04

Reasoning Engine

Performs analytical, predictive, prescriptive, and agentic reasoning on assembled context plus rules.

LYR-03ACT

Layer 3 — Execution Layer

Routes and executes multi-step actions with autonomy and approval controls enforced at runtime.

LYR-03.01

Action Router

Plans sequential, parallel, and conditional execution paths based on context and policy.

LYR-03.02

System Connectors (Action Execution)

Executes idempotent writes with retries, rollbacks, and system-specific safety semantics.

LYR-03.03

Human-in-the-Loop Manager

Routes approvals, escalations, and delegation chains for high-impact decisions.

LYR-03.04

Retry and Error Handling

Classifies transient vs permanent failures and supports compensating action patterns.

LYR-04AUDIT

Layer 4 — Governance Layer

Captures audit evidence, authorizes actions, and provides continuous governance monitoring.

LYR-04.01

Audit Logger

Immutable records for access, decisions, actions, and outcomes with source traceability.

LYR-04.02

RBAC Engine

Role, group, and attribute-based authorization at data and action level.

LYR-04.03

Compliance Reporter

Framework-aligned reporting for SOC 2, ISO, GDPR, HIPAA, and internal policy controls.

LYR-04.04

Monitoring Dashboards

Operational visibility into ingest health, workflow performance, policy events, and system behavior.

SHEET 04Intelligence Maturity ModelL1..L5

From descriptive reporting to agentic execution

assistents.ai is designed to move organizations beyond static insight toward governed operational action.

  1. L1Descriptive

    What happened?

    Historical reporting and dashboards.

  2. L2Diagnostic

    Why did it happen?

    Root-cause analysis requiring manual investigation.

  3. L3Predictive

    What is likely to happen?

    Forecasting likely outcomes from signal patterns.

  4. L4Prescriptive

    What should we do?

    Recommended next actions still requiring manual execution.

  5. L5Agentic

    Consider it done.

    Detection, decision, execution, and audit chain completed with governance controls.

SHEET 05Detailed Workflow ExampleSEQUENCE

Invoice discrepancy resolution

Representative workflow that activates all four layers in a governed loop.

Governed execution loopLive
  1. Detect discrepancy in ERP
  2. Pull original purchase order context
  3. Retrieve and parse relevant contract clauses
  4. Classify variance against policy and thresholds
  5. Create tracking ticket in service system
  6. Notify stakeholders and route approvals
  7. Hold payment pending authorized decision

7 steps · all four layers · payment held pending authorized decision

SHEET 06Deployment OptionsTOPOLOGY

Infrastructure flexibility

Choose deployment topology based on data residency, network, and governance requirements.

TOPO-01

SaaS cloud

Supported
TOPO-02

VPC deployment

Supported
TOPO-03

Private cloud

Supported
TOPO-04

On-premise

Supported
TOPO-05

Hybrid topology

Supported
SHEET 07What to Evaluate NextCHK-01..05

Evaluation checklist for technical and governance teams

Use this list during architecture review and pilot scoping.

  1. Context coverage across structured and unstructured sources
  2. Rule encoding quality for business and compliance logic
  3. Action safety model (approval thresholds and autonomy boundaries)
  4. Auditability and evidence export readiness
  5. Operational reliability under error and retry conditions
SHEET 08Sign-offREADY

Run a technical architecture session on your workflow

We will map data sources, rule logic, execution boundaries, and evidence requirements to a concrete pilot design.

Schedule Technical Review Pilot & Pricing
Document
assistents.ai · Architecture brief
Layers
Data · Intelligence · Execution · Governance
Lead time
Architecture review to pilot · scoped session
Sheet
08 of 08 · How It Works

See the architecture in action

Walk through a live session mapping your data sources, rules, and execution boundaries.

Book a session

Explore the platform

Review how Context Engine, Semantic Layer, and Action Engine work together.

Platform overview