The layer that takes AI from pilot to production.
Supervisor agents plan, specialised agents act inside your core systems; every step is traced, passes human approval where needed, and is costed. Model-agnostic; on-prem, hybrid or cloud.
The agents below are simulations derived from real agent definitions. Pick a sector to watch a different scenario.
Credit card limit increase
- Message received, session identity verified
- Intent: limit increase · Amount: 150,000 · Card: ****4412
Simulation · derived from real agent definitions · every agent can be built by dialogue with the Autonomous Agent and validated with a test corpus
The real problem with AI is not the technology.
Most enterprises are trying something with AI; very few can run it in production, at scale, under control.
The PoC gap
Pilots impress, but the path to production is undefined.
Scattered initiatives
Every unit trials its own tool; no enterprise coherence.
Unmeasured value
The gap between “it works” and “it pays off” goes unreported.
Governance gap
Security, compliance and auditability are afterthoughts.
Result: budget spent, transformation missing.
From consulting to platform, from infrastructure to operations.
A partner that owns enterprise AI transformation and runs it end-to-end. Three components under one roof; accountability in one place.
Expert team
Strategy, data, engineering and change management in one experienced team. Consultants do not come and go; we operate the product with you.
The Aginies platform
An enterprise-grade agentic orchestration layer that runs every AI workload from one place. Not a chatbot; the single execution layer for all of the enterprise’s AI scenarios.
Sovereign infrastructure
Independent operation within national borders with GPU-as-a-Service. Data and model control stay with you; usage-based capacity with no capital outlay.
Every agent starts as a dialogue.
Describe what you need; the Autonomous Agent sets up the supervisor and specialist agents, binds tools and the knowledge base, runs the test corpus and deploys with your approval. Every agent in the library can be produced this way.
Autonomous Agent and the product family →The agent will appear here
- Platform AginiesEverything comes together here
- Visual agent builder: agent, router, memory, guardrail and human-approval blocks
- Autonomous Agent: build agents by dialogue, test corpora, deployment
- Voice AginiesSTT · TTS · ASR
- aginies-voice-tr-v3 (STT), aginies-tts-tr-v2, aginies-asr-stream-v1
- On-prem serving; audio never leaves the enterprise
- Code AginiesIDE Registry · IDE extensions · code completion
- In-house code completion; code never leaves
- IDE Registry: approved extension and model distribution
- Hub AginiesModel Hub · MCP Hub · Model proxy
- aginies-large-c5 · medium-c5 · large-g5 · large-g4 · medium-g4
- aginies-medium-oss-120b · small-oss-32b · vision-oss-72b (on-prem)
- Vision AginiesDocuments · images · masking
- aginies-vision-oss-72b · on-prem
- Field extraction with source document and confidence score
- Dialog AginiesDialogue UI
- The same agent in text and voice channels
- Human takeover and hand-back
What happens per agent, how the platform is doing, what each model costs: one dashboard.
Every run is recorded step by step; every request can be masked and anonymised. Separated by workspace and tenant; teams share and co-develop agents inside the organisation.
- Per-agent success heatmap and error timeline
- Platform health, model usage and cost
- Proxy to cloud models with your own keys, observed from one point
- Masking, anonymisation, full audit trail
Agentic AI executes real business processes in four steps.
- 01
Understand signals
Inputs from applications, APIs, documents, voice channels and events become execution-ready tasks.
ApplicationsAPIsDocumentsVoiceEvents - 02
Supervisor plans
Complex objectives are decomposed into structured steps; responsibilities are assigned to specialised agents.
SupervisorPlanningDecompositionDelegation - 03
Agents act
Knowledge is retrieved, documents processed, tools invoked, and real operations triggered in enterprise systems.
RetrievalTools / MCPActionsIntegrations - 04
Everything is observed
Agent decisions, latency, cost and tool usage are monitored and optimised with full visibility across environments.
TracesLatencyGuardrailsAudit
Eight integrated capability layers.
Built for enterprise scale, governance and resilience. The layers work together, not in isolation.
Explore the platform →Orchestration & Execution Intelligence
Runs complex work end-to-end; routes requests intelligently and keeps multi-step processes stable even when dependencies fail.
BAI / Model Orchestration
Uses the right model for each task; reduces vendor lock-in and keeps operations running when a provider is unavailable.
CKnowledge & Retrieval
Turns fragmented enterprise information into governed, searchable, trustworthy knowledge; answers link back to sources.
DGovernance, Risk & Compliance
Makes AI auditable, safe and fit for regulated environments; every decision is traceable.
EObservability & Optimisation
Provides visibility into accuracy, speed, cost and health; produces the data for continuous improvement.
FIntegration & Connectivity
Connects to enterprise systems and customer channels without rebuilding the existing technology landscape.
GMultichannel Experience & Voice
Delivers AI across digital, messaging and voice channels on one consistent orchestration underneath.
HDeployment & Enterprise Architecture
Supports the on-premise, hybrid and sovereignty requirements of large enterprises.
These are not concepts; they are workloads running live on Aginies today.
E-commerce support & action
Where is my order, returns, delivery changes: actions, not answers.
Read more → Enterprise FunctionsInvoice & document extraction
OCR → validation → ERP: clean records without manual entry.
Read more → InsuranceVoice AI for claims intake
A voice agent takes the loss notice and opens the claim in the system.
Read more → Software DeliverySDLC agent team
PM, analyst, architect, developer and tester agents working together in the CI/CD pipeline.
Read more → BankingConversational banking
Complete mobile banking operations by typing or talking.
Read more → Enterprise FunctionsEmail classification & attachment verification
The inbox reaches the right team; missing attachments are caught before work starts.
Read more →A disciplined transformation methodology.
Not every AI idea deserves to be built, and those that do should not start unprepared. Every use case passes a five-layer assessment; each stage ends at a clear decision point: proceed, fix or stop.
- 01 Value Why should this be done at all?
- 02 Readiness Do we have the inputs we need?
- 03 Feasibility Can we actually build this?
- 04 Operations How will it live after go-live?
- 05 Governance Is it secure, controlled and auditable?
Designed for regulated environments.
AI must meet the same standards as every other critical system. Built to the requirements of regulated sectors such as finance, insurance and healthcare.
Time to move from experimenting with AI to transforming with it.
In a 30-minute discovery session we take your 2–3 priority business problems, show a live demo of a similar scenario, and draft a roadmap that starts with the Value layer.
- Your 2–3 priority problems
- Live demo of a similar scenario
- Roadmap starting with value analysis