Every kind of AI work, under one roof.
Five practices, eighteen services. Agents, models, inference and infrastructure, products, and the strategy and operations around them.
Zingaro AI is a full-stack AI engineering and services company: it builds agentic systems and automation, trains custom language, speech and vision models, engineers inference and deploys on-premise or in-country, ships AI products and voice agents, and runs the systems with people on the queue.
Pick a service. See what it does.
Agents
Agents that plan, act and finish the job.
Autonomous and multi-agent systems that plan, call tools, check their own work and finish the job.
- Agent architecture. Planner, worker and checker roles, memory, state and recovery designed for the job, not copied from a demo.
- Tool use and MCP integrations. Your CRM, ERP, ticketing, databases and internal APIs exposed as tools, with permissions and audit on every call.
- Computer-use and browser agents. For systems with no API: agents that read screens and operate software the way a person would.
Automation
The steps a person repeats every day, run by agents.
The repetitive steps between your systems, run by agents with people on the queue.
- Workflow discovery. A week on the floor with your team. Every repetitive job listed, sized and ranked by value.
- Back-office agents. Invoices, claims, onboarding, orders and tickets processed from arrival to filed record.
- RPA replacement. Rule-based bots that break on every change replaced with agents that handle variation.
Assistants
Assistants that know your business and show their sources.
Assistants and copilots inside your tools, grounded in your data, in your customers’ languages.
- Customer assistants. Support and sales conversations on web, app, WhatsApp and voice, with hand-off to a person when needed.
- Internal copilots. Drafting, summarising and next-step suggestions inside CRM, helpdesk, email and documents.
- Grounding and citations. Every answer traceable to the document or record it came from. No source, no answer.
Language models
Language models trained for your domain, on weights you own.
Domain models fine-tuned, post-trained and distilled on your data, on weights you own.
- Supervised fine-tuning. Domain data, your formats and your tone, on open weights from small to frontier-class.
- Post-training with RL. Preference optimisation and reinforcement learning with verifiable rewards for reasoning, tool use and format discipline.
- Reasoning models. Models that think before they answer, tuned on your problems, with the cost kept under control.
Speech
Speech models for the accents, dialects and lines you actually have.
Speech-to-text and text-to-speech trained on your accents, dialects and line quality, plus real-time speech-to-speech.
- Speech-to-text training. Streaming recognition tuned for narrow-band, noisy, interrupted telephone audio in any language or dialect.
- Text-to-speech and voice cloning. Natural voices that sound like your brand, cloned or designed, in the languages your customers speak.
- Real-time speech-to-speech. Low-latency conversational models for voice agents that listen and speak at the same time.
Vision
Models that see what your people would see, on every frame.
Detection, segmentation, video analytics and vision-language models, from the camera to the edge.
- Detection and segmentation. Objects, defects, people, vehicles and documents, trained on your footage rather than a public dataset.
- Vision-language models. Ask questions of images and video in plain language: what is wrong here, is this step complete, read this label.
- Video analytics. Events in live or recorded video: a gate left open, a queue too long, a safety step skipped.
Data
The dataset nobody else has, built for you.
Datasets, annotation, transcription and synthetic data pipelines, with evaluation sets that reflect production.
- Collection. Speech, text, images and video across the conditions you need, with consent and metadata, including field collection.
- Annotation. Labels, entities, intents, boxes, masks and tracks, with inter-annotator agreement measured.
- Transcription. Native speakers writing dialects the way they are spoken. Najdi and Gulf Arabic, Indian languages, code-switching.
Evals
Know it works before you ship. Know it still works after.
Know whether it works before you ship, and keep it working after: evaluation, safety and observability.
- Evaluation suites. Task sets from your real cases, scored by people and by models calibrated against them, run before every change.
- Red-teaming. Adversarial testing for prompt injection, data leakage, unsafe actions and off-policy answers.
- Guardrails. Input and output checks, tool permissions, refusal rules and rate limits that fit the risk of each action.
Inference
Faster, cheaper inference on the hardware you have.
Serving stacks tuned for latency and cost: quantisation, speculative decoding, batching, caching, GPU planning.
- Serving stacks. The right engine for the model and the hardware, tuned for your traffic pattern rather than the benchmark’s.
- Quantisation and distillation. Smaller, faster models that keep the accuracy your eval suite requires.
- Speculative decoding and caching. Draft models, prefix caching and KV-cache management for lower latency at the same cost.
On-device
AI that runs where the data is made, with nothing sent anywhere.
Small language, speech and vision models running on phones, laptops and edge hardware, with no cloud in the loop.
- Model selection and distillation. Pick the smallest model that does the job, distil from a larger teacher where accuracy needs it, and prove it on your evaluation set.
- Quantisation and compilation. INT8 and INT4 quantisation, pruning where it pays, and compilation for the target: Apple Neural Engine, Qualcomm, Intel and AMD NPUs, Android and iOS, embedded Linux.
- On-device speech. Offline speech recognition and synthesis for apps and devices that cannot depend on a connection, in the languages your users speak.
Deployment
AI that runs where the rules say the data must sit.
On-premise, air-gapped, private cloud and in-country deployment with MLOps, monitoring and retraining.
- On-prem and air-gapped. Installed on machines you own, inside your network, with updates carried in by hand where required.
- Private cloud and VPC. Deployed into your AWS, Azure or GCP account, in your region, under your access controls.
- Sovereign and in-country. Hosting that satisfies data residency rules in the Gulf and elsewhere, with the paperwork to prove it.
Product
AI products, built by a team that runs its own.
AI-native web, mobile and API products, built by a team that ships and runs its own.
- AI-native applications. Products where the model does the work, not a chat box bolted onto a form.
- Developer APIs and SDKs. Speech, document, vision and agent capabilities exposed for your engineers to build on.
- Integrations. CRM, ERP, helpdesk, telephony and payments connected so the product fits your stack.
Voice
Voice agents that answer, book, chase and follow up.
Inbound and outbound voice agents on our own platform and telephony, in your customers’ languages.
- Inbound voice agents. Answer every call, find out what the caller needs, resolve it or route it, and log the outcome in your CRM.
- Outbound campaigns. Reminders, follow-ups, renewals, surveys and collections at volume, with a person for anything sensitive.
- IVR replacement. Replace the menu tree with a conversation.
Knowledge
Answers from your own documents, with the source shown.
Answers from your own documents and systems, with the source shown and permissions respected.
- Ingestion and structure. PDFs, scans, wikis, tickets, email and tables parsed with their structure kept, not flattened.
- Retrieval that works. Hybrid search, reranking and query rewriting, tuned on your questions, measured on your answers.
- Context engineering. The right passages, in the right order, with the right instructions. Most accuracy lives here.
Documents
Documents read, checked and filed. The uncertain ones flagged, not guessed.
Invoices, claims, contracts and forms read, checked and filed into your systems, with uncertain fields flagged.
- Classification and routing. Every incoming document sorted by type and sent to the right queue or folder.
- Extraction. Fields from PDFs, scans, photos and emails, including handwriting and poor scans, with vision-language models where layouts vary.
- Validation. Totals that add up, dates in range, IDs that match your records. Rules you define, checks we run.
Strategy
Not a strategy deck. A list of jobs, with numbers attached.
Find the work worth doing with AI, prove it in weeks, and know what to build versus buy.
- Use case discovery. A week on the floor with your team. Every candidate job listed, sized and ranked.
- Data and feasibility audit. What data exists, where it sits, what the rules allow and what a model can realistically do with it.
- Build, buy or leave. A plain recommendation per job, including when off-the-shelf software is the right answer.
Operations
We run it. You get the report.
We run the systems, hold the review queue and send the weekly report. You see the work, not the tool.
- Running the systems. Monitoring, restarts, updates and retraining. You never touch the tool unless you want to.
- The review queue. Our people check anything uncertain before it reaches you, in your hours, in your language.
- The weekly report. Work delivered, exceptions, what changed and what we recommend next. Short enough to read.
Arabic
Arabic the way it is actually spoken.
Speech, language and agents for Gulf and Najdi Arabic, built and evaluated with native speakers.
- Dialect speech recognition. Najdi, Gulf and other dialects on real telephone audio, trained on recordings collected with native speakers.
- Arabic text-to-speech. Natural Gulf voices, cloned or designed, for agents and announcements.
- Arabic language models. Open-weight models fine-tuned for Arabic dialects, right-to-left formatting and code-switching.
Systems that plan, use tools and finish the job.
3 services
- Agents01Agentic AI developmentAutonomous and multi-agent systems that plan, call tools, check their own work and finish the job.Explore
- Automation02AI workflow automationThe repetitive steps between your systems, run by agents with people on the queue.Explore
- Assistants03Conversational AI and copilotsAssistants and copilots inside your tools, grounded in your data, in your customers’ languages.Explore
Language, speech and vision models trained on your data.
5 services
- Language models04Custom LLM training and fine-tuningDomain models fine-tuned, post-trained and distilled on your data, on weights you own.Explore
- Speech05Custom ASR and TTS trainingSpeech-to-text and text-to-speech trained on your accents, dialects and line quality, plus real-time speech-to-speech.Explore
- Vision06Computer vision and multimodal AIDetection, segmentation, video analytics and vision-language models, from the camera to the edge.Explore
- Data07Data, labelling and synthetic dataDatasets, annotation, transcription and synthetic data pipelines, with evaluation sets that reflect production.Explore
- Evals08Evals, red-teaming and guardrailsKnow whether it works before you ship, and keep it working after: evaluation, safety and observability.Explore
Serving that is fast, cheap and inside your boundary.
3 services
- Inference09Inference engineering and optimisationServing stacks tuned for latency and cost: quantisation, speculative decoding, batching, caching, GPU planning.Explore
- On-device10On-device and edge AISmall language, speech and vision models running on phones, laptops and edge hardware, with no cloud in the loop.Explore
- Deployment11Enterprise and sovereign AI deploymentOn-premise, air-gapped, private cloud and in-country deployment with MLOps, monitoring and retraining.Explore
AI-native applications, shipped and maintained.
4 services
- Product12AI product and platform developmentAI-native web, mobile and API products, built by a team that ships and runs its own.Explore
- Voice13Voice agent developmentInbound and outbound voice agents on our own platform and telephony, in your customers’ languages.Explore
- Knowledge14Knowledge systems, RAG and enterprise searchAnswers from your own documents and systems, with the source shown and permissions respected.Explore
- Documents15Document AI and intelligent processingInvoices, claims, contracts and forms read, checked and filed into your systems, with uncertain fields flagged.Explore
Knowing what to build, then running it.
3 services
- Strategy16AI strategy and transformationFind the work worth doing with AI, prove it in weeks, and know what to build versus buy.Explore
- Operations17Managed AI operationsWe run the systems, hold the review queue and send the weekly report. You see the work, not the tool.Explore
- Arabic18Arabic-first AISpeech, language and agents for Gulf and Najdi Arabic, built and evaluated with native speakers.Explore
The techniques that matter this year, and what we do with them.
The field moves every quarter. This is what we are building with now, in plain words.
- 01
Agentic systems
Models that plan, call tools and finish multi-step jobs.
Agents with MCP tool access, checkers and human hand-off, in production.
- 02
Computer-use agents
Agents that operate software through the screen.
For legacy systems with no API, with strict permissions.
- 03
Reasoning models
Models that think before answering, at a cost.
Fine-tuned on your problems, routed only where they pay off.
- 04
RL post-training
Reinforcement learning with verifiable rewards.
Format, tool use and correctness trained in, not prompted.
- 05
Small models and distillation
One job, one small model, a fraction of the cost.
Distilled from large teachers, served on your hardware.
- 06
Inference optimisation
Quantisation, speculative decoding, caching, routing.
Latency and cost engineered against your own load tests.
- 07
Real-time speech
Speech-to-speech models that listen and talk at once.
Voice agents that do not talk over people, in dialects.
- 08
Vision-language models
Ask questions of images and video in plain language.
Inspection, reading and video events, on the edge.
- 09
On-device models
Small models running on phones, laptops and NPUs, with no cloud in the loop.
Distilled, quantised and shipped inside your app, with a hybrid path for the hard cases.
- 10
Context engineering
Retrieval done properly beats bigger prompts.
Structure-aware retrieval with citations and permissions.
- 11
Evals and guardrails
Measuring quality before and after every change.
Task suites from your cases, red-teaming, drift alerts.
- 12
Synthetic data
Model-generated examples where real data is scarce.
Generated, reviewed by people, never used for evaluation.
- 13
Sovereign AI
Models and data kept in-country, on your hardware.
Air-gapped and in-region deployments for regulated sectors.
Scope first. Then a price for the work, not for seats.
Fixed-scope build
A pilot or a product, scoped, fixed fee, billed on milestones. Nothing upfront.
Retained AI team
Engineers and researchers on your roadmap, month to month, inside your tools.
Managed operations
We run the systems, priced on the volume we actually handle. It moves with your work, not your headcount.
No seat licences, no minimum users, no annual lock-in. We quote once we have seen the work, and every milestone is invoiced only when it is accepted.
Tell us the job. We will tell you which service it is.
Twenty minutes is enough to say whether we can take it.
A pilot starts within 5 working days of agreed scope · Nothing upfront · No seat licences