Platform

One platform. Every layer of AI execution.

Build agents, manage knowledge, observe executions, connect systems. All from a single, production-grade control plane. Aginies is not a chatbot; it is the execution layer where all of the enterprise’s AI scenarios run.

Platform facts derived from the library

The numbers come from scenario definitions, not from copy.

The 77 live scenarios in the agent library are read at build time; the figures and distributions below are derived from those definitions and change as scenarios are added.

77live scenarios

14sectors

261specialist agents

657distinct tools

200systems connected

73approval rules

127write steps in systems

3,320,970simulated runs / month

Channel distribution (scenarios)

api37

app34

web29

whatsapp27

email27

batch25

voice23

sms5

branch3

Step kinds (all steps)

write127

tool call110

reason109

verify89

notify80

ingest77

human approval61

plan48

retrieve38

Model families (agent assignments)

aginies-tulpar83

aginies-sunkar78

aginies-talay71

aginies-konrul21

aginies-voice-tr8

Autonomous Agent

Build the agent by dialogue; test it, approve it, deploy it.

Describe what you need: the Autonomous Agent sets up the supervisor and specialist agents, connects tools and the knowledge base, picks the models, writes and runs the test corpus, and deploys with your approval. Everything in the agent library can be produced through this dialogue; runs are observed in logs and the dashboard.

Autonomous AgentAginies Workspace · Dialogue banking: voice and text transaction assistant

Message the Autonomous Agent…

AgentTestsLive

The agent will appear here

Test corpus: by suite, scenario and turn; golden path, branches, robustness injection
Check families: customer resolved, PII before verification, state machine, memory round-trip, judge dimensions
Coverage report: which checks score, which are blind
Changes are versioned; deployment always stops at a human approval
Logs, conversations and the dashboard are queried from the same dialogue

Product family

7 products, one platform.

Platform Aginies is the umbrella; Voice, Code, Hub, Vision, Workforce and Dialog are its modules. Same governance, same logs, same licence.

Platform Aginies

Everything comes together here

Orchestration core, visual agent builder, Autonomous Agent, knowledge base, logs and dashboards. The single control plane where every agent is built, observed and governed.

Visual agent builder: agent, router, memory, guardrail and human-approval blocks
Autonomous Agent: build agents by dialogue, test corpora, deployment
Knowledge base: document pipeline, versioning, chunk editor
Logs and dashboards: live runs, conversations, per-agent success heatmap
Workspace and tenant separation: teams share agents inside the organisation and build together
Monitoring: what happens per agent, platform health, model usage and cost
Reports: scheduled cost, performance, SLA and audit reports by unit, channel and branch
Templates, users, licences

What is included

Visual agent builder, workspace and tenant management, roles via SSO
Execution engine, approval cards, kill-switch, dashboards and reports
Knowledge-base management and the Autonomous Agent

Integration

With the organisation’s identity provider (SAML/OIDC), SIEM, data warehouse and ticketing.

Governance

A separate policy set per workspace; four-eyes rule and versioning platform-wide.

77 / 77 scenarios use it

Platform Aginies · Dashboard · last 30 daysall workspaces · all tenants

executions13,120,000

success97.4%

p50 latency1,4 s

platform healthhealthy

busiest agents · each cell ≈ 1 day

dialog_banking_assistant%97.4

card_debt_payment%99.1

kvkk_data_detection%96.2

kvkk_document_masking%98.8

motor_claim_end_to_end%98.1

merchant_operations%100

model usage

aginies-tulpar-438%

aginies-talay-229%

aginies-sunkar-119%

aginies-voice-tr-v39%

cloud · proxy$2.960

cost · by scenario

Dialogue banking26%

Credit & onboarding24%

Claims operations18%

KVKK masking14%

Merchant ops10%

Other8%

PII masking: onanonymisation: onaudit trail: full1,920+ active agents

Voice Aginies

STT · TTS · ASR

Speech models trained for Turkish: streaming speech-to-text, natural text-to-speech and real-time ASR. Voice agents through call-centre SIP integration.

aginies-voice-tr-v3 (STT), aginies-tts-tr-v2, aginies-asr-stream-v1
On-prem serving; audio never leaves the enterprise
Voice analysis: quality scoring, sentiment and intent

What is included

Streaming Turkish ASR and STT (aginies-voice-tr-v3), natural TTS (tts-tr-v2)
Voiceprint verification, spoken OTP, warm hand-off
Call quality analysis: transcript, sentiment, compliance checks

Integration

SIP with Genesys, Avaya and open-source switches; API with recording systems.

Governance

Recordings in-country; identity level and transaction threshold per channel.

23 / 77 scenarios use it

Voice Aginies · SIP · call 0212-…-4471aginies-voice-tr-v3 · on-prem

customerSomeone hit my car last night, plate 34 ABC 123, I want to report a claim.

agentSorry to hear that. I found your policy by plate; can I take the location and time?

STT180 ms

intentclaim intake · 0.97

sentimentcalm

TTS · aginies-tts-tr-v2ASR · stream-v1PII masking: on

Code Aginies

IDE Registry · IDE extensions · code completion

For engineering teams: IDE extensions and code completion, an enterprise IDE registry, and the SDLC agent team (PM, analyst, architect, developer, tester) in the CI/CD pipeline.

In-house code completion; code never leaves
IDE Registry: approved extension and model distribution
SDLC agents work with Jira, Git and CI

What is included

IDE extensions (VS Code, JetBrains) and in-house code completion
IDE Registry: approved extension and model distribution, version pinning
SDLC agent team: analysis, design, development, test, review

Integration

With Jira, Git (GitHub, GitLab, Bitbucket, self-hosted), CI/CD and static analysis tools.

Governance

Code never leaves the organisation; PR merge and production deployment always with people.

8 / 77 scenarios use it

Code Aginies · billing-service/invoices.tscompletion · on-prem

14export async function exportInvoicePdf(id: string) {
15  const invoice = await repo.findById(id);
16  if (!invoice) throw new NotFound('invoice');
17  const pdf = await renderer.render('invoice', maskPii(invoice));
18  await audit.log('invoice.export', { id, user: ctx.user });
19  return storage.put(`invoices/${id}.pdf`, pdf);
20}

Tab: acceptPROJ-4821coverage 87%SAST ✓

IDE RegistryVS Code · JetBrains extensionDeveloper Agent · PR #2291

Hub Aginies

Model Hub · MCP Hub · Model proxy

Model catalogue: Aginies model families fine-tuned on enterprise data from Qwen, GLM and Kimi bases (tulpar, talay, sunkar, konrul) plus the current open releases of the same bases, on in-country GPUs. The catalogue is kept current: a new release is added to the Hub when it ships, the previous one stays for the contract term. Enter your own keys and let the platform reach cloud models as a proxy: single-point management, usage and cost tracking, masking. MCP Hub: approved tool servers.

aginies-tulpar-4 · talay-2 · sunkar-1 · konrul-1 (fine-tuned families, on-prem)
Current open releases of Qwen, GLM and Kimi in the same catalogue; aginies-voice-tr-v3 and tts-tr-v2 for speech
Model proxy: cloud models with your own keys, observed and masked from one point
Switch models with one selection; fallback strategy

What is included

Model catalogue: tulpar, talay, sunkar, konrul families and current open releases
Model proxy and key management; usage and cost tracking
MCP Hub: approved tool servers, invocation policies, connection tests

Integration

With in-country GPU pools; with the organisation’s chosen cloud model providers through the proxy.

Governance

Model and tool changes versioned and gated by tests; keys in an encrypted vault.

77 / 77 scenarios use it

Hub Aginies · Model Huball workspaces · October 2026

model	access	usage · last 30 days	cost
aginies-tulpar-4	on-prem · GPU 4×	58%	—
aginies-talay-2	on-prem · GPU 2×	84%	—
aginies-sunkar-1	on-prem · GPU 1×	91%	—
aginies-konrul-1	on-prem · vision	22%	—
qwen · current release	on-prem · open model	31%	—
aginies-voice-tr-v3	on-prem · STT	47%	—
cloud · proxy	your key	12%	$288

keys encrypted · never shown to usersall requests maskedMCP Hub · 14 servers

Vision Aginies

Documents · images · masking

Image and document understanding: invoice, contract and form extraction, damage-photo assessment, visual quality control. Personal-data detection and document masking run on the same models.

aginies-konrul-1 · images and documents · on-prem
Field extraction with source document and confidence score
Personal-data detection and document masking

What is included

Invoice, contract, form and ID document extraction; per-field confidence
Damage-photo assessment and visual quality control
Personal-data detection and document masking

Integration

With document stores (S3, SharePoint), scanners and ECM; results written to ERP and claims systems through tools.

Governance

Documents processed inside the perimeter; source document and extracted value stored together.

21 / 77 scenarios use it

Vision Aginies · invoice_2026_1012.pdfaginies-konrul-1 · on-prem

extracted fields

Invoice noFTR-2026-1012

Date12.10.2026

KDV%20 · 3.125,00

Total18.750,00 TL

TCKNmasked (KVKK)

source: page 1confidence ≥ 0.95

Workforce Aginies

Agent workforce, on demand

Outsourced agents instead of outsourced people: roles such as iOS developer, business analyst, accountant and test engineer are hired as agents that work inside your tools. Every task, output and hour-equivalent in the work log; a named team lead on the Aginies side.

Role catalogue: engineering, business analysis, finance, support, HR, legal
Work log: task, output, hour-equivalent, quality score, review status
Shadow period → sampled review → autonomous; thresholds and kill-switch
Agent-month or output-based billing; you own the outputs

What is included

Role catalogue: engineering, business analysis, finance, support, HR, legal
Work log: task, output, hour-equivalent, quality score, review status
Shadow period → sampled review → autonomous; a named team lead

Integration

With the organisation’s own tools: Jira, Git, ERP, ticketing, e-mail.

Governance

Production and financial record changes under the organisation’s approval; the organisation owns the outputs.

17 / 77 scenarios use it

Workforce Aginies· roster and work log · fintech-opsMon 09:00

Dialog Aginies

Dialogue UI

The dialogue surface for customers and employees: web widget, mobile, WhatsApp and messaging. Session memory, human takeover and an audit trail for every message.

The same agent in text and voice channels
Human takeover and hand-back
Conversation dashboard and quality scoring

What is included

Web and mobile dialogue UI; embeddable widget
WhatsApp, SMS and e-mail channels with the same agent
Approval cards, file and image sharing, warm hand-off

Integration

With the organisation’s identity and OTP stack; with the WhatsApp Business API and SMS gateways.

Governance

Per-transaction identity threshold; every conversation and transaction in the trace.

60 / 77 scenarios use it

Dialog Aginies · web widgetcard_debt_payment v2

I want to pay my full card balance from my current account.

Your statement balance is 24,860, due 14 October. Current account ****7741 has enough balance. If you confirm I will send a one-time code.

✓ get_card_debt · get_accounts · policy: no approval needed

Confirm.

Code sent. Once entered, the payment executes instantly and you get a confirmation.

session memoryhuman takeover: readyaudit trail

Type a message…↑

Architecture

Wherever it needs to run.

Same platform, same governance; different perimeter. Switch the deployment mode to see where the sovereign boundary falls.

Platform, models and data inside the enterprise data centre. No external dependency; the Aginies model families and open releases are served in-house.

Conceptual view. Component names and responsibilities are shown; implementation details are shared in a discovery session.

Capability layers

Eight layers, one execution model.

Orchestration & Execution Intelligence

the engine layer

Runs complex work end-to-end; routes requests intelligently and keeps multi-step processes stable even when dependencies fail.

Supervisor → sub-agent → supervisor architecture
Dynamic agent routing
Stateful multi-step execution
Agent-to-agent communication (A2A)
Scheduled and webhook triggers
Agent templates
Autonomous Agent: build agents by dialogue with test corpora

Scope

Supervisor plan, agent assignment and result merge; retry and fallback path on a failed step
Stateful execution: session and long-term memory, pending approvals, timeout rules
Parallel branches and loops; condition-based termination

Governance

Each agent’s authority is defined per tool; the supervisor cannot call out-of-scope tools.

Evidence

The run plan and every step’s input/output in the trace; replayable.

AI / Model Orchestration

brain selection and resilience

Uses the right model for each task; reduces vendor lock-in and keeps operations running when a provider is unavailable.

Multi-model gateway
Model proxy: single-point, observable access to cloud models with your own keys
Model switching without redesign
Fallback model strategy
On-prem serving for open-source models
Prompt testing environment and versioning
Hub Aginies: enterprise fine-tuned models (c5, g5, g4, oss) and speech models

Scope

Hub catalogue: fine-tuned families on Qwen, GLM and Kimi bases (tulpar, talay, sunkar, konrul) and current open releases
Model proxy: cloud models with the organisation’s own keys, single-point observation and masking
Per-scenario model choice, fallback model and prompt versioning

Governance

Model changes are versioned and never reach production without passing the test corpus.

Evidence

Model version, tokens and cost recorded per request; catalogue history.

Knowledge & Retrieval

enterprise memory

Turns fragmented enterprise information into governed, searchable, trustworthy knowledge; answers link back to sources.

Document embedding pipeline
Versioned knowledge base management
Tag-based document segmentation
Hybrid search and multi-source RAG
Chunk-level inspection and editing
Hallucination-reduction architecture
Knowledge base management: sources, tags and access policy

Scope

Document embedding pipeline, chunk inspection and tagging; versioned knowledge base
Access policy at chunk level: who may see which document through which agent
Cited answers; “I don’t know” when there is no source

Governance

Knowledge-base changes are approved by the owner; the previous version can be restored.

Evidence

Chunks and their versions used in every answer; coverage and quality report.

Governance, Risk & Compliance

the control layer

Makes AI auditable, safe and fit for regulated environments; every decision is traceable.

Guardrails and policy engine
Human-in-the-loop checkpoints
Agent decision traceability
Sensitive data masking and PII redaction
Masking and anonymisation of all requests
Full input/output logging and audit trail
Kill-switch and automation limits

Scope

Guardrails and policy engine: input/output checks, masking, forbidden actions
Human-approval checkpoints: threshold, approver, timeout; approval card on mobile and web
Kill-switch per user, team and organisation; role-based authorisation

Governance

Policy changes under the four-eyes rule; every rule versioned with a reason.

Evidence

Approval records (who, when, what), guardrail interventions and kill-switch events.

Observability & Optimisation

performance management

Provides visibility into accuracy, speed, cost and health; produces the data for continuous improvement.

Per-run traces and timelines
Latency and token tracking
Cost attribution by scenario, unit and channel
Usage and cost per model; platform health
Routing accuracy measurement
Dashboard and analytics layer
Live logs, conversation records, per-agent success heatmap
Reports: scheduled, exportable (PDF, XLSX, CSV); internal audit template

Scope

Per-run trace: step, duration, tokens, tool call, error
Dashboards: agent success heatmap, platform health, model usage, cost attribution
Forwarding to SIEM and data warehouse; alert rules

Governance

Traces are immutable and retained according to policy.

Evidence

One-click audit sample; monthly quality report per agent.

Integration & Connectivity

enterprise reach

Connects to enterprise systems and customer channels without rebuilding the existing technology landscape.

REST API and database integrations
Model Context Protocol (MCP) servers
Custom tool definitions and invocation policies
Native connectors: email, calendar, files, collaboration tools
Web widget and messaging integrations
MCP Hub: catalogue of approved tool servers

Scope

REST, databases and MCP servers; invocation policy per tool
Ready connectors: core banking, ERP, CRM, ticketing, payments, switch
Read/write separation; write tools require approval by default

Governance

Each tool defined with a service account and scope; secrets kept in the organisation’s vault.

Evidence

Tool-call log: parameters (masked), response code, duration.

Multichannel Experience & Voice

customer interaction layer

Delivers AI across digital, messaging and voice channels on one consistent orchestration underneath.

Real-time speech-to-text and streaming voice processing
Call-centre SIP integration
WhatsApp, SMS and email services
Intent detection and entity extraction blocks
Session memory
Dialog Aginies: dialogue UI, human takeover
Voice Aginies: Turkish STT, TTS and ASR models

Scope

Dialog Aginies on web and mobile; WhatsApp, SMS and e-mail channels
Voice Aginies: streaming ASR, Turkish STT/TTS, call centre over SIP
The same agent on every channel; warm hand-off and conversation summary

Governance

Identity level and transaction threshold defined per channel.

Evidence

Transcripts, recordings and summaries under the retention policy; quality score per channel.

Deployment & Enterprise Architecture

fit to enterprise constraints

Supports the on-premise, hybrid and sovereignty requirements of large enterprises.

On-premise and air-gapped deployment
Hybrid architecture: sensitive workloads inside, elastic capacity outside
Private cloud / dedicated region
SSO / SAML, fine-grained RBAC, workspace isolation
Per-tenant agent sharing and collaborative development
GPU-as-a-Service for in-country elastic capacity

Scope

Sovereign shared (our data centres in Türkiye), dedicated tenant/GPU, on-prem or air-gapped in the organisation’s data centre
Access: VPN tunnel or allowlist over the internet
In-country elastic capacity with GPU-as-a-Service

Governance

Change management and incident notification in the contract; remote maintenance in windows the organisation opens.

Evidence

Network diagram, tunnel/allowlist configuration, backup and drill records.

Visual agent builder

Design agent pipelines without writing glue code.

Drag, connect, configure. Every block, from agents and routers to memory, guardrails and human approval, is a first-class primitive you compose into any workflow. Business and IT look at the same screen.

Agent

A specialist with its own model, tools and memory.

Supervisor

Breaks the objective into steps, delegates to agents, merges the result.

Router

Branches the flow by intent, rule or score.

Memory

Shares session and long-term context across agents.

Guardrail

Checks input and output against policy; blocks or masks.

Human approval

Pauses on critical decisions, presents to the authorised person, records the decision.

Tool / MCP

Read or write to an enterprise system; invocation policy per tool.

Parallel & loop

Runs independent steps simultaneously and repeated work until a condition is met.

Monitoring and reports

Every run is visible, step by step.

What happens per agent, the health of the platform, which model is used how much and what it costs, on one dashboard. A step-by-step record of every run: input, output, model, duration, tokens, approver. Every request can be masked and anonymised; everything is separated by workspace and tenant.

Per-agent executions, success and error heatmap
Platform health: latency, queues, GPU and model availability
Usage and cost per model, including cloud models through the proxy
Cost attribution by scenario, unit and channel
Masking and anonymisation on every request
Workspace / tenant separation; teams share and co-develop agents
Reports: scheduled cost, performance, SLA and audit reports; PDF, XLSX, CSV; delivered by email and shared folder
One report for internal audit: model version, rule set, user

Platform Aginies · Dashboard · last 30 daysall workspaces · all tenants

executions13,120,000

success97.4%

p50 latency1,4 s

platform healthhealthy

busiest agents · each cell ≈ 1 day

dialog_banking_assistant%97.4

card_debt_payment%99.1

kvkk_data_detection%96.2

kvkk_document_masking%98.8

motor_claim_end_to_end%98.1

merchant_operations%100

model usage

aginies-tulpar-438%

aginies-talay-229%

aginies-sunkar-119%

aginies-voice-tr-v39%

cloud · proxy$2.960

cost · by scenario

Dialogue banking26%

Credit & onboarding24%

Claims operations18%

KVKK masking14%

Merchant ops10%

Other8%

PII masking: onanonymisation: onaudit trail: full1,920+ active agents

Platform Aginies · Reportsall workspaces · October 2026

monthly executions · last 12 monthslast 30 days: 13,120,000+31% YoY

report	breakdown	schedule	format
Monthly cost report	scenario · unit · channel · branch	1st of month · 07:00	PDF · XLSX
Agent performance	success, latency, error classes	weekly · Monday	PDF
Audit export	run traces, approvals, model versions	on demand	CSV · JSON
Model usage	tokens, cost and proxy share per model	daily · 06:00	XLSX
SLA and capacity	p95 latency, queues, GPU occupancy, projection	weekly	PDF

delivered by email and shared folderinternal audit templatepersonal data masked

Workforce Aginies · Roster and work logworkspace: fintech-ops · this week · tenants separate

agent	role · team	hour-eq.	output	quality	mode
ios-dev-01	iOS Developer · mobile team	14 h	9 PRs · 21 points	4.7	autonomous · 10% review
qa-01	QA Engineer · mobile team	31 h	412 tests · 6 bugs	4.8	autonomous · 10% review
ba-01	Business Analyst · payments product	9 h	11 stories · 2 processes	4.5	shadow · 100% review
acct-01	Accountant · finance	27 h	238 entries · 3 reconciliations	4.9	autonomous · threshold-approved

work log · today

09:12ios-dev-01PR #4821 opened: payment screen accessibility fixes · 2 tests addedreview pending

09:40acct-0138 supplier invoices processed, 2 out of tolerance → to m.ozkan for approvalapproval

10:05qa-01Regression round 3: 412/412 · 1 new bug (BUG-2291) filed with evidencedone

10:30ba-01Story PAY-118 with 6 acceptance criteria written → to the product ownerreview

weekly timesheet exportedbilling: agent-monthteam lead: e.demir (Aginies)

Integration

Plug in any tool with MCP.

Add a server URL, configure headers, test the connection: agents can invoke its tools securely. With chunk-level control, every piece of knowledge is inspectable, editable and tagged.

serverhttps://mcp.erp.internal/v1connected

toolsget_purchase_order · post_invoice · get_vendor

policypost_invoice → human approval > 50,000

authSSO · workspace: finance-ops

chunks4.212 · tag: policy/v3

Integration catalogue

200 systems in 12 kinds: the enterprise systems the scenarios touch.

Each row is a system kind with its examples from the library. Connecting a new system means one tool definition and one invocation policy.

Enterprise APIs76 connections

Access ControlAppointment SystemBank SIM-Swap Signal APICI PipelineCI Runner (GitHub Actions)CI/CDCI/CD (signed artefacts)Card Management+55

Customer channels50 connections

Customer PortalHangar Tablet AppMicrosoft TeamsMobile App ChatOTP / SMS GatewayPush & SMS GatewaySMS GatewayShift Channel (Teams)+6

Core systems44 connections

Active Directory / Entra IDBSS / BillingBilling (Amdocs)Billing (CIS)CLM (Contract Lifecycle Management)Card ManagementClaims SystemCore Banking+19

Databases and vectors44 connections

Audit LogCollections PlatformControl & Sanctions Lists (vector)Eligibility Criteria (vector)Fleet RegistryGIS / Network ModelGIS / Zoning PlanKYC / Customer 360+29

Ticketing and work orders25 connections

CMMSCMMS (Maximo)Case ManagementField ServiceITSM / IncidentJiraJira (QA)Jira / Xray+6

ERP and MES25 connections

Billing / CIS (SAP IS-U)Billing / SettlementERPERP (SAP / Logo)ERP (SAP GTS)ERP BillingERP Spare PartsInventory+12

E-mail20 connections

E-mailEmailEmail (Exchange)Exchange / M365 MailProcurement Inbox

Document stores19 connections

ConfluenceContract RepositoryDocument StoreDocument Store (S3)Tech Pub Repository (S1000D)

CRM8 connections

CRMCustomer CRM / BillingCustomer ProfileHubSpotSalesforce CRM

Payment systems7 connections

Bank APIPSP / Acquirer APIPayment Gateway (iyzico)Payment HubRefund ServiceSettlement Ledger

Voice and switch6 connections

Call Centre SIPGenesys SIPIVR / SIP

HR systems3 connections

LMSSAP SuccessFactorsWorkday

Operations

How it is run after go-live.

Targets are settled with the organisation in the contract; the items below are the platform’s standard operating model.

Versioning and rollback

Agent definition, rule set, prompt and model version recorded together; rollback to the previous version is one step.

Test corpus gate

Every change passes the suite/scenario/turn test corpus before production; the coverage report is recorded.

Continuity targets

Target RTO 4 hours and RPO 1 hour on the sovereign shared deployment; set with the organisation on dedicated and on-prem. Backups inside Türkiye.

Model catalogue upkeep

When a new base release ships, the fine-tune is repeated and a new catalogue version opened; the previous one stays for the contract term.

Incident management

Notification times by severity in the contract; kill-switch with the organisation, root-cause report with Aginies.

Monthly review

Per-agent quality, cost and approval rates; threshold and rule updates together with the organisation’s administrator.

Deployment models

One platform, three deployments.

From sovereign shared to air-gapped; access over a VPN tunnel or an allowlist. Details on the security page. Security →

recommended startSovereign shared

Our data centres in Türkiye, an isolated workspace for the organisation, access over VPN.

Starts within days
Model updates and capacity handled by Aginies
Fixed IPs, isolated tenant, SIEM forwarding

higher isolationDedicated tenant / GPU

A tenant and GPU pool reserved for the organisation in the same data centre; encryption with the organisation’s own key on request.

No resource sharing
Organisation-specific model versions
Capacity commitment by contract

full controlOn-prem in the organisation’s data centre

Hub, model servers and Platform in the organisation’s own data centre; remote maintenance only in windows the organisation opens.

No data leaves the organisation’s perimeter
Requires the organisation’s GPU investment
Installation and updates follow the organisation’s change calendar

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.

Book a 30-minute discovery session → dahi@aginies.com

Your 2–3 priority problems
Live demo of a similar scenario
Roadmap starting with value analysis