ZeevTech Solutions is an AI development company that builds chatbots, autonomous agents, and document automation on top of OpenAI and Claude models. Projects start at $1,499 and typically ship in 3 to 6 weeks. We integrate with the CRM, helpdesk, and databases you already run.
AI automation is the use of large language models to complete work that previously required a person reading, classifying, or writing text — answering support questions, extracting fields from documents, drafting responses, or routing requests — inside an existing business workflow rather than as a standalone chat window.
What does an AI development company actually build?
An AI development company builds working software around a language model, not the model itself. That means the retrieval layer that feeds it your data, the guardrails that keep answers accurate, the integrations into your CRM or helpdesk, the human review step, and the monitoring that shows what it got wrong.
Support chatbots grounded in your own documentation and ticket history
AI agents that take actions — book, update, escalate — not just reply
Document processing: invoices, contracts, forms, and ID extraction
Internal search and question answering over company knowledge
Content and reporting automation wired into existing tools
How much does AI automation cost?
AI automation projects start at $1,499 at ZeevTech Solutions. A support chatbot grounded in your documentation typically costs $1,499 to $5,000. Document processing pipelines and multi-step agents run $5,000 to $20,000. Model usage is billed separately by the provider and is usually a small monthly amount.
We recommend starting with one narrowly scoped workflow that has a measurable cost today — a queue of repetitive tickets, or a stack of invoices someone keys in by hand. That gives a defensible before-and-after number within weeks rather than a vague transformation programme.
How do you stop an AI chatbot from making things up?
We ground answers in your own content using retrieval-augmented generation: the model is given the relevant source passages at query time and instructed to answer only from them, citing the source. Anything outside that scope is routed to a human. Confidence thresholds and refusal behaviour are configured explicitly, not left to chance.
We also log every question and answer so you can review real failures. A chatbot without an answer log cannot be improved, because nobody knows what it is getting wrong.
Which AI models do you build on?
We build primarily on OpenAI and Anthropic Claude APIs, choosing per workload rather than by default — reasoning quality, context window, latency, and cost per token all differ. We keep the model behind an abstraction layer so switching providers later is a configuration change, not a rewrite.
Is our business data safe when using AI?
Yes, when configured correctly. We use enterprise API endpoints where provider terms exclude your data from model training, keep personal data out of prompts where it is not needed, and can route sensitive workloads to a self-hosted open model instead. Data handling is documented before the build starts.
How do you measure whether AI automation worked?
We agree the metric before writing code — tickets deflected, minutes saved per document, response time, or error rate — and instrument it from day one. Every deployment reports against that baseline. If a workflow does not move its metric within the first month, we change the approach or recommend stopping.
How we deliver ai development & automation
1
AI audit3–5 days
We map your workflows and identify which ones have a measurable, automatable cost today.
2
Proof of concept1–2 weeks
One workflow built end to end against real data, with a measured baseline.
3
Grounding & guardrails1–2 weeks
Retrieval setup, prompt design, refusal behaviour, and human review path.
4
Integration1–2 weeks
Wiring into your CRM, helpdesk, database, or internal tools.
5
Evaluation3–5 days
Test set of real cases scored before launch, with a pass threshold agreed up front.
6
Monitor & tuneOngoing
Answer logging, failure review, and iterative prompt and retrieval improvements.
Technologies we use
OpenAI API
Anthropic Claude API
Node.js
Python
Vector databases
LangChain
PostgreSQL
Redis
AWS
Proof
AI Development & Automation We Have Shipped
Live products you can open and verify, plus platforms running in production today.
Enterprise Software
Enterprise ERP & CRM Platform
A unified operations platform — CRM pipeline, HRMS, inventory management, and analytics dashboards with role-based access and a full admin panel, from sales floor to leadership.
React
Node.js
MySQL
AWS
FAQ
AI Development & Automation FAQs
Straight answers on cost, timelines, ownership, and delivery for ai development company.
How much does it cost to build an AI chatbot?
AI chatbot development starts at $1,499. A support chatbot grounded in your own documentation typically costs $1,499 to $5,000, while document processing pipelines and multi-step agents run $5,000 to $20,000. Model API usage is billed separately by the provider and is usually a modest monthly cost.
How long does an AI automation project take?
Most AI automation projects ship in 3 to 6 weeks. A grounded support chatbot takes 3 to 4 weeks including evaluation, and a document processing pipeline with human review takes 5 to 8 weeks. We start with one narrowly scoped workflow so you see a measurable result inside the first month.
Will the AI give wrong answers to my customers?
Any language model can be wrong, so we design for it. Answers are grounded in your own content through retrieval, the model is instructed to answer only from supplied sources and cite them, out-of-scope questions route to a human, and every exchange is logged so real failures can be reviewed and fixed.
Do you use OpenAI or Claude?
Both, chosen per workload rather than by habit — reasoning quality, context window, latency, and token cost differ meaningfully between them. We keep the model behind an abstraction layer, so changing provider later is a configuration change rather than a rewrite of your application.
Is my company data used to train AI models?
No, when configured correctly. We use enterprise API endpoints whose terms exclude customer data from model training, and we keep personal data out of prompts wherever it is not required. For sensitive workloads we can run a self-hosted open model instead so data never leaves your infrastructure.
Can AI automation integrate with our existing CRM or helpdesk?
Yes. We integrate with the tools you already run — including HubSpot, Zoho, Zendesk, Freshdesk, and custom internal systems — through their APIs or webhooks. The AI works inside your existing workflow rather than becoming another separate tool your team has to check.
How do we know whether the AI is actually saving money?
We agree the success metric before writing code — tickets deflected, minutes saved per document, or response time — and instrument it from day one against a measured baseline. You get a report against that number. If it does not move within the first month, we change approach or tell you to stop.
