AI for People
Assistants that help your teams find information and finish work, inside the tools they already use and within existing permissions.
SIZH IT Solutions helps businesses build intelligent AI applications, autonomous agents, custom software and secure digital platforms that turn complex challenges into practical business outcomes.
An AI system is only as good as the engineering around it. We cover the model work and the software, cloud, security and data work that makes it usable in production.
Goal-driven agents that call your tools and complete multi-step work under guardrails.
ExploreGrounded answers and generation from your approved content, with citations.
ExplorePhone and chat agents that resolve enquiries and book work into your systems.
ExploreApplications shaped around your process, with code and infrastructure you own.
ExploreStorefronts, portals and cross-platform mobile apps built to be maintained.
ExploreInfrastructure as code, pipelines and monitoring your team can operate.
ExploreApplication, API, cloud and AI security review and hardening.
ExplorePipelines, dashboards and integrations that keep systems consistent.
ExploreIt is an operating decision, not a technology purchase: routinely asking whether a workflow belongs to a person, to plain code, or to a model with oversight — and having the engineering capability to act on the answer.
Assistants that help your teams find information and finish work, inside the tools they already use and within existing permissions.
Intelligent automation of the repetitive, multi-system workflows that currently need a person to carry work between steps.
AI capability built into your customer-facing applications and SaaS platforms, where it genuinely differentiates the product.
We look at volume, rule stability and tolerance for error, and tell you whether AI is the right tool or whether plain code is cheaper.
We check the data actually exists, is accessible and is good enough, before anyone commits to a build.
A narrow build on your real data with an agreed quality bar, so the decision to proceed is evidence-based.
Connect it to the systems the work touches, reusing your authentication and permission model.
Staged rollout with evaluation in CI, cost and latency dashboards, and a rollback path.
We start from the workflow, not the model. Each engagement targets a specific, high-volume job where an agent measurably beats the status quo.
Goal-driven agents that plan, call your tools and complete real multi-step work with human oversight.
Explore service 02 Revenue and serviceAlways-on digital agents that answer, qualify, book and resolve across WhatsApp, web, voice and email.
Explore service 03 Grounded answersRetrieval systems that answer strictly from your approved documents, with citations and no invention.
Explore service 04 Operations at scaleEnd-to-end business processes run by cooperating agents across the tools you already pay for.
Explore service 05 Conversational telephonyNatural-sounding phone agents that handle calls, qualify callers, book appointments and log outcomes.
Explore service 06 Production foundationsThe engineering under the intelligence: APIs, data pipelines, evaluation, security, cost control and monitoring.
Explore serviceOne virtual agent trained on your business, live on WhatsApp, your website, voice and email. It answers in seconds, qualifies properly, books the meeting and resolves the repetitive work — then hands over to your team with full context.
Responds in seconds, qualifies against your criteria and books the demo before interest cools.
Resolves the repetitive majority from approved content and escalates the rest cleanly.
Covers nights, weekends and peaks so no call or message is missed.
Takes the booking, confirms it and sends the reminders.
Agents that respond first, qualify properly and keep the pipeline moving.
Resolution rather than deflection, with clean escalation when a person is needed.
The coordination work that quietly consumes your team's week.
Hiring and people operations without the administrative drag.
Accuracy, evidence and audit trails — the areas where guessing is unacceptable.
Production capacity and research depth, inside your brand rules.
The layers stay consistent; what sits in each one is chosen per use case. We do not force every project through a single stack, and we will use plain code wherever it is cheaper and more reliable than a model.
Your databases, documents, wikis, tickets and transactional records — the sources an answer or action must be grounded in.
Ingestion, chunking, embedding, hybrid retrieval and the API connections into the systems that hold the truth.
Versioned prompts, task-appropriate model routing and durable orchestration of multi-step work.
Typed tools under scoped credentials, so the system can take real action idempotently rather than only describe one.
Permission-aware retrieval, least-privilege credentials, approval gates on consequential steps and full audit logging.
Evaluation sets in CI, tracing, cost and latency dashboards, drift alerting and a defined rollback path.
Resolve the repetitive majority of enquiries from approved content, around the clock.
ExploreAnswer every enquiry in seconds, qualify against your criteria and book the meeting.
ExploreSales, support, bookings and notifications on the channel your customers already use.
ExploreAnswer every call, take the booking, log the outcome and transfer when a person is needed.
ExploreBehaviour-triggered sequences with content production and consent enforced in the sending path.
ExploreMulti-system processes that complete without a person carrying work between steps.
ExploreA ride-hailing and fleet management platform, now with agentic dispatch, driver support and demand intelligence.
View productA configurable multivendor service-booking marketplace with agentic onboarding, matching and support.
View productA classifieds marketplace with agentic listing creation, moderation and buyer-seller matching.
View productMost clients start with a pilot to prove the case, then move to a production build. Others simply hire our engineers and direct the work themselves.
Prove it works on your data before you commit.
One workflow, one agent, built on your real data with a genuine go/no-go decision at the end. The fastest honest answer to “will this work for us?”
An agent your team can depend on in production.
Full build of a production agent: integrations, guardrails, evaluation, monitoring and handover. Scoped and priced up front against agreed milestones.
Engineers who work as part of your team.
Named engineers assigned to you, working your hours in your tools. You direct the roadmap; we supply the capability. One week minimum.
We keep your agents healthy and improving.
Monitoring, quality review, tuning and cost control for agents already in production — plus a reserved block of hours for improvements each month.
We built, sold and ran eight commercial platforms before we built agents for anyone else. That shapes how we scope, test and hand over.
A narrow agent that reliably owns one job beats a broad assistant that demos well and fails on Monday. We would rather ship one agent that works than five that need babysitting.
If a rules engine or a plain integration is cheaper and more reliable, we say so on the first call. We have talked clients out of AI projects — it is why they come back.
Every agent ships with a fixed evaluation set and an agreed quality bar. We can tell you how often it is right, with evidence, before you go live.
We have built, sold and supported eight commercial platforms. We know what breaks at 3am, because we have been the ones fixing it.
Agents connect to the CRM, ERP, helpdesk or legacy system you already run — through APIs, webhooks or bridges where no API exists.
An agent is a system to run, not a project to finish. Monitoring, tuning and cost control continue once the build is done.
We connect to your CRM, helpdesk, ERP and channels through their APIs — and build bridges where no API exists.
Systems fail when they are built as demos. We build them as systems — scoped, evaluated, monitored and owned. Security, maintainability and integration are part of the architecture, not a phase before launch.
Process walkthroughs, data review, constraints and a written scope you sign off before build.
Data model, integration boundaries, hosting and the security model, agreed up front.
A narrow build on your real data against an agreed quality bar, so the go-ahead is evidence-based.
Two-week increments, each ending in a working deployment and a review.
Automated coverage on critical paths, evaluation sets for AI behaviour, acceptance testing with your users.
Staged rollout into your infrastructure with monitoring and a tested rollback path.
Quality, cost and latency tracking after launch, with handover documentation or an ongoing retainer.
Agentic dispatch, conversational booking and passenger service for mobility operators.
Explore sectorProvider onboarding, listing assistance, moderation and two-sided support agents.
Explore sectorEnquiry qualification, viewing scheduling and listing generation at portfolio scale.
Explore sectorPre-sales advice, order self-service, returns handling and catalogue enrichment.
Explore sectorVoice order taking, reservations, reminders and guided upsell without aggregator fees.
Explore sectorIntake qualification, document Q&A, scheduling and internal knowledge assistants.
Explore sectorAppointment booking, reminders, triage intake and patient follow-up with human oversight.
Explore sectorRoute planning, proactive status updates, exception handling and technician support.
Explore sectorA connected ride-hailing system spanning customer journeys, driver operations and fleet administration.
02A multivendor booking foundation for businesses offering services through a shared marketplace.
03A structured marketplace that helps sellers publish listings and buyers discover relevant offers.
04A public-facing digital experience for a nationally recognized performing arts venue.
An agent is software that is given a goal, a set of tools it may use and rules it must follow. Rather than answering one question, it plans the steps, calls your systems, and either completes the work or escalates with context. The difference from a chatbot is that an agent takes action.
A working proof of concept on your real data typically takes one to three weeks. A production deployment with integrations, evaluation and monitoring is usually four to ten weeks depending on how many systems it must touch.
We build retrieval-grounded systems that answer from your approved sources with citations, and we test them against a fixed question set before launch. Where the agent is not confident, it says so and escalates rather than guessing.
We design the data boundary with you first. Options range from provider APIs with no-training commitments to deployment inside your own cloud account. Retrieval is permission-aware, so the agent cannot surface what a user may not see.
Yes. Agents connect through APIs, webhooks, databases or RPA where no API exists. We have integrated CRMs, ERPs, helpdesks, calendars, payment systems and bespoke legacy platforms.
Running cost is driven by conversation or task volume and the models used. We route each task to the cheapest model that passes your quality bar, cache aggressively and give you a cost dashboard, so spend stays predictable.
One week — a 40-hour block with a dedicated engineer. From there you can extend into monthly, quarterly or ongoing retainer arrangements.
Yes. You own all code, prompts, configuration and documentation we produce for you, and we hand over the repositories and infrastructure at the end of the engagement.
Let's evaluate your requirements and design a practical, secure and scalable solution for your business. We will tell you honestly whether AI is the right tool, and outline what a first build looks like.