Most "AI features" die in a demo because nobody budgeted for the boring part — evals, guardrails, and what happens when the model is confidently wrong. We build the AI into your software and the plumbing that keeps it working after launch.
Senior US-led leadership under CTO Jashan Jeet Singh · 10 years, 100+ projects · 500+ businesses served across US, UAE, Saudi & India
Vizion Tools is an AI software development company that builds custom AI-powered software — LLM applications, AI agents, and machine-learning features — from prototype to production. A senior, US-led team runs every engagement, with delivery through experienced teams in Egypt and India; day one, we tell you which parts of the build are genuinely AI risk and which are ordinary engineering, because most of the cost is the second thing.
Here's the four shapes it usually takes, and what changes about how we build each one.
If your product needs to answer questions from your own data, hold a conversation, or draft something a human used to write by hand, this is retrieval-augmented generation or a fine-tuned workflow — not "just call the OpenAI API and hope." We design the retrieval pipeline, pick and test the model, and build the eval harness that tells you when an answer is wrong before your customer does.
An agent that can take actions — file a ticket, update a record, call another API — is a different engineering problem than a chatbot that only talks. We scope exactly what the agent is allowed to do, build the guardrails around it, and instrument it so you can see what it decided and why, not just what it said.
Sometimes the right tool isn't a large language model at all — it's a trained classifier, a forecasting model, or a computer-vision pipeline that's cheaper and more accurate for the specific job. We'll tell you when a smaller model beats an LLM on cost and latency, because it usually does.
Most AI value right now isn't a new product — it's AI wired into the CRM, portal, or internal tool you already have. We integrate model APIs into existing software without a rebuild, and we're honest about where that integration needs new infrastructure versus a weekend of plumbing.
Looking to automate internal operations instead of building AI into a product? That's a different engagement — see how we automate internal workflows with AI transformation. Need to package this as a mobile or web app rather than a backend feature? We also build AI-powered mobile & web apps.
End-to-end delivery when you want us to own the build, dev pods when you want a dedicated team inside your process, or staff augmentation when you just need senior AI engineers slotted into a team you already run.
Every engagement is scoped and reviewed by US-based senior leadership, including CTO Jashan Jeet Singh — not a rotating account manager. Delivery execution runs through experienced teams in Egypt and India.
You see what's built, what's in progress, and what's blocked — in real time, not in a weekly status email that's already stale.
The model prompts, the eval suite, the pipeline code, the trained weights where applicable — all of it transfers to you, fully documented, at handoff.
Validating the idea before committing to the full build? Start with an MVP instead, then expand scope once it's proven. Want that kind of senior oversight dedicated to your team full time? See senior technical leadership as a fractional CTO engagement.
Across custom software, ERP, and now AI-specific builds — including the mistakes that taught us evals aren't optional.
AI is new to the market; the engineering discipline behind it isn't new to us.
AtoZ Wholesale, f1Agronomy, Schreiber Foods, Intuit, Safeplus, and VCare have all shipped software with us.
CTO Jashan Jeet Singh has spent 10+ years running and scaling tech teams from 5 to 50 people — he reviews the scope on your project, he doesn't just sign off on someone else's.
Founders and CEOs running teams of roughly 10 to 100 people who want AI genuinely inside their product — not a slide that says "AI-powered," an actual feature customers rely on. You've usually already tried the free tier of a model API and hit the point where "it mostly works" isn't good enough to ship.
Already have a working AI prototype that a tool like Lovable, Replit, or Bolt helped you get to? You don't need this page — you need us to harden an AI-built prototype for production instead of building it from scratch.
There's no honest flat rate for this — the cost swings on how much of the build is genuinely novel AI engineering (custom retrieval, agent guardrails, model evaluation) versus straightforward integration work. Two projects that both say "add an AI chatbot" can land at very different prices depending on what's actually behind that sentence.
We scope that difference on a free call, then give you a fixed price on the defined scope before any work starts — not an open hourly clock. Payments are milestone-based, tied to what's actually delivered, and you own 100% of the IP the moment it ships.
We define the actual outcome you need, which data and systems the AI touches, and — critically — how you'll know if it's wrong. If nobody can answer that last question yet, that's the first thing we fix.
We build the retrieval pipeline, agent logic, or model integration against real data, not a curated demo set. You see progress in the tracker, not in a reveal at the end.
This is the part most "AI features" never get: an eval suite that scores output quality, guardrails that catch the failure modes we found in testing, monitoring for inference cost and latency in production, and a plan for what happens when the model is confidently wrong — because it will be, eventually.
AI software development is the design and engineering of custom software that uses artificial intelligence — large language models, machine learning, or AI agents — to deliver a specific business outcome. It covers everything from building the AI capability itself (retrieval, model selection, agent logic) to the production engineering that makes it reliable: evaluation, guardrails, and monitoring once real users are on it.
There's no fixed price because scope varies too much — a simple chatbot integration and a custom multi-step AI agent are not the same build. We scope your project on a free call, then quote a fixed price on that defined scope before any work starts, billed in milestones tied to delivered work rather than hours.
Timelines run from a few weeks for a focused MVP-style feature to a few months for a full production build with agents or custom ML models. The scoping call is where we give you a real timeline based on what you're actually building, not a generic industry estimate.
Yes. We support private and self-hosted model deployments where required, and your data is never used to train anyone else's model. Your data stays yours, in infrastructure you control or approve, and access is scoped to what the AI feature actually needs.
Vizion Tools is led by a senior, US-based team under CTO Jashan Jeet Singh, headquartered in New Britain, Connecticut, with global delivery through experienced teams in Egypt and India. Product and project accountability sits in the US on every engagement; day-to-day build work runs through our global delivery pods.
Both. We build new AI software from scratch — LLM apps, agents, ML features — and we also take AI-built prototypes from tools like Lovable, Replit, or Bolt and harden them for production: adding the evals, security, and monitoring a fast prototype usually skipped.
We're model-agnostic — OpenAI, Anthropic, and open-source models are all options, and we pick based on what actually fits your accuracy, latency, and cost requirements, not on which vendor we prefer. Part of the job is telling you when a smaller, cheaper model beats a flagship one for your specific use case.
A free scope review is a 30-minute call with a senior engineer and our CTO. No obligation, no inflated scope.
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