What people ask, answered straight.

Zingaro AI is an AI-native services company. It builds the agents, trains the models, engineers the inference and runs the systems for clients in the United States and the Middle East, on the client's own servers when the data cannot leave, from an engineering team in India. It sells the work, scoped on a call and billed on milestones, not software seats.

An AI-native services company does the work rather than selling software to do it. Models and agents are the workforce, people are on oversight, and the client pays for the outcome delivered into the systems it already uses. Zingaro AI is one, and it also trains the models and engineers the infrastructure the work runs on.

Zingaro AI takes on every kind of AI work that ships: agentic systems, workflow automation, assistants and copilots, custom LLM, speech and vision models, data and evaluation work, inference engineering, enterprise and sovereign deployment, AI products, voice agents, knowledge systems, document AI, strategy and managed operations.

An engagement with Zingaro AI starts with a twenty-minute call about one job. If the job fits, a one-to-two-week discovery lists and ranks the candidate jobs and puts a number on the first one. Then a fixed-scope pilot builds it on the client's real data.

A Zingaro AI pilot starts within 5 working days of the scope being agreed.

A Zingaro AI pilot is fixed scope and fixed fee, runs 4 to 6 weeks, and produces real output on the client's real data, measured against a number written down before it starts. At the end the new value of that number sits next to the old one; that is the whole review.

Models that Zingaro AI fine-tunes on a client's own data are delivered to the client and run on the client's infrastructure where the rules require it. The statement of work for each build records the ownership and licence terms. There are no seat licences and nothing that stops a client taking the work in-house with the runbooks.

Zingaro AI and CallWhiz AI are separate brands of the same company. Zingaro AI, at zingaro.ai, is the services company that builds, trains and runs AI systems for clients. CallWhiz AI, at callwhiz.ai, is the voice agent platform Zingaro AI built and runs, with its own website, pricing and documentation; Zingaro AI uses it to deliver voice agent work. RingTrunk, at ringtrunk.com, is the same company's product for Indian phone numbers and SIP trunks.

Zingaro AI builds and runs voice agents for inbound and outbound calls: appointments, verification and status, reminders and collections, first-line questions from a knowledge base, and warm hand-off to a person. It trains the speech models on the client's own line quality and dialects, and operates its own phone numbers and SIP trunks in India through RingTrunk.

Zingaro AI trains custom models: fine-tuning and reinforcement post-training of language models, distillation of large models into small ones, custom speech-to-text and text-to-speech for a language or dialect, and vision models for inspection, reading and video events. Every model is measured against an evaluation set the client agrees represents correct.

Zingaro AI uses both, chosen per job. Hosted frontier models are used where the data may leave and breadth matters; open-weight models fine-tuned and served by Zingaro AI are used where privacy, cost, latency or a narrow domain wins. Often a router decides per request, sending the common cases to a small model and the rest to a larger one or a person.

Zingaro AI builds computer vision and multimodal systems: visual inspection, reading documents and forms, counting and tracking, and events from video, deployed on servers or on edge devices where the cameras are.

Inference engineering is the work of serving a trained model fast and cheaply enough for production: quantisation, batching, speculative decoding, caching, routing between models and sizing the hardware. Zingaro AI does this on the client's own GPUs or in the client's cloud, measured with load tests on the client's real traffic.

Zingaro AI takes over AI systems built by others under managed AI operations. It starts with an audit of the evaluation suite, monitoring and failure modes, then runs the system with people on the exception queue, a weekly report and retraining when the data drifts.

Zingaro AI deploys on the client's own servers, including air-gapped and in-country installations. That is a normal deployment for the company, not an exception, and it is built first for banking, insurance, healthcare and government.

A sovereign deployment by Zingaro AI means the model weights, the inference, the logs and the keys all stay inside the client's boundary, and model updates arrive as signed packages the client's team verifies and installs. Air-gapped means the same with no outbound network connection at all.

During a Zingaro AI pilot the data stays where the client says it may stay: on the client's servers, in the client's private cloud account, or in Zingaro AI's managed environment. Where a hosted frontier model is used for part of the work, that is agreed in writing before the pilot starts.

Zingaro AI is accountable when a model or agent it runs gets something wrong. Uncertain work goes to a human queue before it reaches the client, every run is logged so it is clear which agent or person did what, and evaluation suites catch regressions before a release.

Zingaro AI supports English, Arabic dialects and the common Indian languages out of the box. Any other language or dialect is trained for the client on the client's own recordings.

Zingaro AI does not publish prices because the cost depends on the work. The scope is set on a call and quoted after. Builds are milestone-based with nothing upfront, and managed operations are priced on the volume actually handled. There are no seat licences.

Zingaro AI has no seat licences, no minimum number of users and no annual lock-in. A fixed-scope build is priced for the work; managed operations move with the volume, not the headcount.

Zingaro AI invoices a fixed-scope build by milestone, and only when the milestone is accepted. Nothing is paid upfront. Managed operations are invoiced on the volume handled in the period.

Zingaro AI signs non-disclosure agreements and works under the client's security requirements, including access reviews, audit logging and deployments where no data leaves the client's network.

Zingaro AI is not a wrapper around a hosted model. It trains and serves its own language, speech and vision models where the job needs them, engineers the inference they run on, and uses hosted frontier models only where breadth matters and the data may leave. The difference shows in deployment: a wrapper cannot run air-gapped.

Models do make things up, which is why Zingaro AI never lets an uncertain answer reach a customer unchecked. Answers are grounded in the client's own documents, every uncertain item goes to a person on a review queue, evaluation suites gate every release, and every run is logged.

Most failed AI projects chose a job with no number, no edges and no recovery path. Zingaro AI starts by choosing a job that has all three, writes the number down before building, and puts people on the exceptions from day one, so the system can go live before it is perfect and earn its way to autonomy on evidence.

Zingaro AI's engineering team is in India and works in the client's hours. The Gulf overlaps most of the Indian working day, and United States clients are covered across mornings and evenings; the live clocks on the site show the overlap at any moment.

Zingaro AI works with mid-sized businesses and enterprises alike. Sovereign deployment, audit logs, evaluation gates and security reviews are capabilities available to any client, not an entry requirement, and a pilot is the same size for both.