We build custom AI chatbots that answer from your knowledge base, take real actions in your systems and hand off to a person with full context, in English, your customers' own language or both.
Chatbots answer from your content and systems, cite sources and say when they don't know.
Conversations in your customers' languages, with right-to-left interfaces designed in from the start.
SSO, audit logs and PII redaction, built to support your SOC 2 and ISO 27001 audits.
As an AI chatbot development company, we start with what the chatbot needs to resolve, not where it will sit. Our AI chatbot development services cover website chat for sales and support, in-app assistants for mobile and web products, in-product help inside SaaS platforms, and internal chatbots that answer HR, IT and policy questions. Each one is grounded in your content through retrieval, so it answers from your documents rather than guessing.
Useful chatbots also act. They check order status, book appointments, create tickets, update CRM records and collect details before a handoff. We connect them to your systems through APIs and webhooks, and when a conversation needs a person, the chatbot passes the full transcript and context so your team doesn't start from zero.
Off-the-shelf chatbot builders are a good fit when you need FAQ answers on a website, your content lives in a few public pages, and the vendor's integrations already cover your stack. They are quick to start, and if that describes you, try one first.
Custom AI chatbot development makes sense when the chatbot must take actions in your own systems, respect user permissions, run in your cloud or region, handle more than one language properly, or fit inside your product's interface. You own the code, prompts and data, and you aren't limited by what a vendor's roadmap supports. On the scoping call, we'll tell you which side of that line you're on.
Enterprise AI chatbot development adds requirements a marketing chatbot never meets. Employees sign in with SSO and see only the documents their role allows. Every conversation, retrieval and action is recorded in an audit trail. Personal data is detected and redacted before it reaches a model or a log, and data stays in the cloud region you choose.
We design for the reviews your security and compliance teams will run: access controls, retention policies, model provider terms and incident handling, built to support your SOC 2, ISO 27001 or HIPAA audits. For regulated workflows, the chatbot can route sensitive cases straight to a person instead of answering them itself.
Many businesses serve customers in more than one language, often in the same conversation. A multilingual AI chatbot needs more than translation: model selection tested on real queries in each language, retrieval that works across languages, replies in the register your customers expect, and, for languages such as Arabic or Urdu, a right-to-left interface that handles text, numbers, dates and mixed-language messages correctly.
We benchmark models on your real questions in each language before choosing one, and build test sets per language so quality is measured for each. Where a language reads right to left, the chat interface is designed for RTL from the start, with mirrored layouts and correct rendering of mixed-direction text across web, mobile and messaging channels.
Timeline depends on the number of knowledge sources, the actions the chatbot must take, the channels it runs on, language requirements and enterprise controls such as SSO. A chatbot that answers from a clean help center is a much smaller project than one that books, refunds and updates records across three systems in two languages.
Pricing is fixed per pilot or milestone and agreed before work starts, after a free 20-minute scoping call. Many teams start with a fixed-price pilot covering one channel and the most common conversation types, measure resolution and handoff quality, then expand. Model costs are separate, estimated up front and kept down with routing and caching.
A free 20-minute call, then a review of real transcripts or tickets to find what the chatbot should resolve.
Build retrieval over your content and connect the systems the chatbot needs to take actions.
Run evaluation sets of real questions, in every language you support, with a demo every week.
Go live on one channel, review conversations and handoffs, then expand to more channels and intents.
Templates, broadcast campaigns, inbox, chatbots and payments on the official WhatsApp Business API — sending at scale for real brands.
A multi-number WhatsApp inbox where sales and support teams work every conversation with full customer context.
Auto-replies to comments and DMs, sends links and captures leads on the official Instagram API — so brands sell while they sleep.
Prove value on one high-impact workflow before you commit further.
Design and ship a complete AI-native product, ready for launch.
A senior team embedded with yours, working in your time zone.
Yes. We build one chatbot backend with shared knowledge, actions and logs, then connect it to each channel: a web widget, an in-app interface for iOS and Android, and messaging channels such as WhatsApp through the official Business API. Behavior can differ by channel while answers stay consistent everywhere.
We test candidate models on your real customer messages, including regional dialects and mixed-language text, before choosing one. Evaluation sets cover every language you support, so quality is measured separately for each. Where a model struggles with certain phrasing, we adjust retrieval, prompts or routing rather than accept weaker answers in one language.
It's designed not to. Answers come from retrieved content with sources, the chatbot says it doesn't know when the evidence isn't there, and it hands off to a person for anything outside its scope. An evaluation suite checks accuracy and faithfulness before every release, and production logs let you review any answer.
Identity, permissions and accountability. Employees sign in with SSO, retrieval respects their role, personal data is redacted before model calls, and every conversation and action is logged. It runs in your cloud and region, built to support your SOC 2, ISO 27001 or HIPAA audits, and connects to your existing ticketing and HR systems.
You do. The code, prompts, knowledge pipelines and evaluation sets live in your repositories, the chatbot runs in your cloud account, and 100% of the IP transfers to you. If you later move the work in-house or to another partner, you keep everything needed to run and change it.
Use a builder if it covers your needs; it's faster. Hire a team when the chatbot must act inside your systems, respect permissions, support several languages or RTL properly, run in your cloud or live inside your product. In those cases the integrations and controls are most of the work, and a builder's limits show up quickly.
Book a free 20-minute scoping call. Share a sample of real conversations, and we'll show what a chatbot could resolve and what a pilot would cover.
