Feature × Audience

How do telcos deploy multimodal AI with Plugsky's architecture?

Telcos deploy multimodal AI on Plugsky by keeping customer documents, field photos and call recordings inside a controlled pipeline: extraction runs in an adapter you own, while reasoning, retrieval and actions run on live OpenAI-compatible chat completions, embeddings and function calling. Region-locked planes plus VPC, on-prem or air-gapped deployment keep traffic in-market, and audio, images and files endpoints are still coming soon.

Key facts

Telco fitPer-market data planes with routing across 30+ models
Live endpointsChat completions with streaming, function calling, JSON mode and embeddings
Coming soonAudio, images, files and batch endpoints are labelled coming soon
ResidencyRegion-locked planes: EU (Frankfurt), GCC (UAE), APAC (Singapore), US (Virginia)
DeploymentPlugsky cloud, your VPC, on-prem and air-gapped for sovereign sites
PricingFlat monthly self-serve plans; enterprise scale scoped on the pricing page
AuditInference, key and admin events exportable to SIEM
Free planplugsky-micro and plugsky-lite, no card; 14-day full-access trial

TL;DR

  • Normalise billing documents, field photos and recordings in an extraction adapter you control.
  • Run reasoning, retrieval and actions on live OpenAI-compatible endpoints.
  • Pin each market's traffic to a region-locked plane or bring the platform on-prem.
  • Route high-volume classification to small models and escalate only hard cases.
  • Export inference and key events to your SIEM for operational and regulatory review.

How it works, step by step

  1. Map the workflows worth automating — billing dispute triage, field photo inspection, call summarisation, multilingual care replies — and rank them by volume and risk.
  2. Decide the data path per market: region-locked Plugsky plane, your VPC, on-prem or air-gapped for the most sensitive sites.
  3. Build an ingestion and extraction layer for documents, images and audio, keeping the OCR or speech engine swappable while file endpoints are coming soon.
  4. Use JSON mode to produce schema-stable records for OSS, BSS and CRM systems, and function calling to invoke approved internal APIs.
  5. Ground agent answers in network documentation and product catalogues with the embeddings API, namespaced per line of business.
  6. Route the bulk of classification and routing to plugsky-micro or plugsky-lite, escalating hard cases through the same endpoint.
  7. Stream inference, key and admin events to your SIEM, then pilot in one market before expanding.
1Map the workflowsworth automating —billing dispute2Decide the datapath per market:region-locked3Build an ingestionand extractionlayer for4Use JSON mode toproduceschema-stable5Ground agentanswers in networkdocumentation and6Route the bulk ofclassification androuting to

Try it yourself

Open the AI workload router simulator →

Where multimodal AI pays off for a telco

Telecoms run on mixed-format data: scanned contracts, PDF invoices, field photos of masts and cabinets, call recordings, chat transcripts and network logs. Multimodal AI turns that into structured records — dispute categories, fault codes, asset conditions, churn signals — and then into actions in OSS, BSS or CRM systems.

The economics come from volume. Most traffic is classification, routing and short summaries that belong on small models, with a minority of hard cases — complex disputes, root-cause analysis, multilingual retention offers — going to larger ones. One OpenAI-compatible endpoint with 30+ models makes that tiering a configuration change rather than a platform migration.

Reference architecture for a multi-market rollout

Ingest at the edge of your own network, then extract: documents and images through an OCR or vision adapter, audio through speech-to-text you control while Plugsky's audio, images and files endpoints remain coming soon. Normalise to text and structured JSON, then call live chat completions for reasoning and the embeddings API for retrieval against market-specific knowledge bases.

Actions flow back through function calling into approved internal APIs — create a fault ticket, credit an account within policy, queue a callback. Because the surface is OpenAI-compatible, your gateway, SDK, retry logic and observability stack stay in place across markets and environments.

Sovereignty, scale and operational honesty

Pin each market to a region-locked plane — EU (Frankfurt), GCC (UAE), APAC (Singapore) or US (Virginia) — and use VPC, on-prem or air-gapped deployment where regulation or network topology demands it. Keep keys per system and environment, export authentication and key lifecycle events to your SIEM, and review retention terms in the DPA.

Capacity-plan around peak-hour traffic and stream anything customer-facing. Be explicit in design reviews about endpoint status: chat, streaming, JSON mode, function calling and embeddings are live, while audio, images and files are roadmap items. See the live pricing page for plan and enterprise scoping.

Honest comparison

ConcernPlugskyHyperscaler model APIsBuilding in-house
Market residencyRegion-locked planes plus VPC, on-prem and air-gappedRegion choice varies by serviceWherever you deploy
Model routing30+ models, switch by name on one APIMultiple services and SDKsServe and tune each model
Actions in OSS and BSSFunction calling into approved APIsPossible with custom glueAll integration is yours
Volume economicsFlat monthly self-serve plans, fair-use usagePer-token spend scales linearlyGPU capex plus ops
AuditInference, key and admin events to SIEMVendor-specific loggingYou build the trail

Frequently asked questions

Can we keep call recordings and customer data in-country?

Yes. Pin workspaces to a region-locked plane for each market, or deploy in your VPC, on-prem or air-gapped. Keys and logs should stay in the same jurisdiction as the data.

Which endpoints are live for telecom workloads?

Chat completions with streaming, function calling and JSON mode, plus embeddings, are live. Audio, images, files and batch endpoints are labelled coming soon.

How do we integrate with OSS and BSS?

Use function calling so the model emits structured tool calls your middleware executes against approved internal APIs, keeping credentials and permissions inside your systems.

How do we control cost at national scale?

Route classification, routing and summarisation to plugsky-micro or plugsky-lite, reserve larger models for complex cases, and monitor usage per key.

Is there an SLA for enterprise deployments?

Review the published SLA and terms for the deployment scope you choose; enterprise agreements cover the specifics, and plan details are confirmed during scoping.

How do we start without a full transformation programme?

Pick one market and one workflow, build on the free plan where appropriate, and measure handling time and accuracy before scaling out.

Does the API work with our existing OpenAI tooling?

Yes. It is OpenAI-compatible, so existing SDKs, gateways and evaluation harnesses keep working after a base URL and model-name change.