01
Customer support chatbots
Deflect repeat questions, hand off to a person with full context, and plug into Zendesk, Freshdesk or Intercom.
FIG 01 · AI Chatbot Development
AI chatbot development services, trained on your data
Custom GPT, Claude and open-model chatbots for support, sales and internal teams. Grounded in your content, connected to your systems and tested before launch.
See how it works
FIG 02 · Quick answer
What are AI chatbot development services?
AI chatbot development services design, build and integrate chatbots that answer questions in natural language using large language models and your own content. Elgrith builds custom RAG chatbots for customer support, sales and internal knowledge, connects them to your CRM, helpdesk and WhatsApp, and tests them for accuracy, hallucinations and data privacy before launch.
- AI models in Kenerate AI, our flagship build
- 200+
- Projects delivered since 2015
- 1,000+
- Clients served
- 250+
- Your code, prompts and content
- 100%
FIG 03 · Why it matters
AI is taking the first line of service.
From Salesforce’s State of Service (2025) and Zendesk’s CX Trends 2025.
01
50%
Of service cases handled by AI by 2027
By 2027, AI is expected to handle half of all customer service cases, up from 30% when the report was published.
Source: Salesforce, State of Service 2025(opens in a new tab)02
75%
Of CX leaders expect AI resolution
75% of CX leaders expect 80% of customer interactions to be resolved without human intervention.
Source: Zendesk, CX Trends 2025(opens in a new tab)03
51%
Were slowed by security concerns
51% of service leaders say security concerns have delayed or limited their AI initiatives. That is why we design for privacy first.
Source: Salesforce, State of Service 2025(opens in a new tab)
FIG 04 · Definition
What a modern AI chatbot does
A modern AI chatbot uses a large language model (LLM) to understand questions in plain language and retrieval-augmented generation (RAG) to answer from your approved content, with citations. Rule-based bots still have a place, and many of the best bots are hybrids.
| AI chatbot (LLM + RAG) | Rule-based bot | Hybrid | |
|---|---|---|---|
| How it works | Understands free text and answers from your documents | Follows buttons, keywords and decision trees | Rules for fixed flows, AI for open questions |
| Best for | Support, sales and knowledge questions asked many ways | Short, fixed flows: order status, opening hours, bookings | Regulated flows that also need open Q&A |
| New questions | Handled, within your content | Only what was scripted | Handled outside the scripted paths |
| Upkeep | Update the content; tune with evals | Edit every flow by hand | Both, with each part kept simple |
| Risk to manage | Hallucination: solved with retrieval, citations and tests | Dead ends that frustrate users | Clean handoffs between the two |
If a rule-based bot covers your top questions, we will tell you. It is cheaper to run.
FIG 05 · What you get
AI chatbot development services
Six ways we put a chatbot to work: for your customers, your sales team and your own staff, on the channels they already use.
02
Sales and lead-qualification chatbots
Answer product questions, qualify visitors, book calls and sync every conversation to your CRM.
03
Internal knowledge assistants
HR, IT and policy answers for staff, with SSO and permission-aware retrieval, so people only see what they are allowed to see.
04
WhatsApp, Slack, Teams and voice bots
One assistant across your website, the WhatsApp Business API, Slack, Microsoft Teams and the phone.
05
Enterprise AI chatbot development
Private deployments on Azure OpenAI, Amazon Bedrock or open-weight models, with audit logs and regional hosting.
06
AI chatbot app development
In-app assistants for your web and mobile products, built into the screens your users already know.
Deliverables
12
deliverables, in writing
Included in every build, written into your fixed quote before work starts.
FIG 06 · Channels
One assistant, everywhere your users are
The same knowledge, tone and rules on every channel, connected to the systems that hold the answers.
- Website
- Slack and Teams
- Voice
Your chatbot
- Help center
- Policies and docs
- Helpdesk
- CRM
Website chat
- Best for
- Support and pre-sales questions
- Connects to
- Help center, product data, CRM
WhatsApp Business
- Best for
- Orders, bookings and updates on the go
- Connects to
- WhatsApp Business API, order system
Slack and Microsoft Teams
- Best for
- Internal HR, IT and policy answers
- Connects to
- SSO, intranet, shared drives
Voice
- Best for
- Call deflection and after-hours lines
- Connects to
- Telephony, booking and helpdesk
Inside your app
- Best for
- Guided onboarding and in-product help
- Connects to
- Your app’s API and user data
E-commerce assistant
- Best for
- Product finder, sizing and order status
- Connects to
- Catalog, inventory and orders
FIG 07 · Flagship build
Proof: Kenerate AI
Kenerate Agent is a production AI chat experience we designed and engineered: users chat, and the agent picks the model and runs the workflow. Behind it, 200+ models live in one app.
- Kenerate Agent: chat with an agent that picks the model and runs the workflow for you
- 200+ AI models in one app, with one login and one credit balance
- Works inside Claude, ChatGPT, Cursor and 19+ AI apps through MCP and CLI
- 23+ studios and tools, with 500+ guides for every use case
Home: one prompt box for image, video and musicDesigned and engineered by Elgrith
- AI models in one app
- 200+
- Studios and tools
- 23+
- Maximum output
- 4K
- Guides
- 500+
FIG 08 · Accuracy
How we keep answers accurate
A chatbot that makes things up costs more than no chatbot. Accuracy is designed, tested and monitored.
06principles
Answers from approved sources
The bot retrieves passages from content you have approved and answers from them, not from guesswork.
Citations in answers
Answers link to the page or document they came from, so users and your team can check them.
“I don’t know” is allowed
When the answer is not in your content, the bot says so and offers a person instead.
Eval sets of real questions
We collect real questions from your inbox, tickets and search logs, with the right answers, and score every change.
Hallucination and regression tests
Automated tests catch made-up answers and anything a change made worse, before release.
Human review
Low-confidence answers are flagged for your team to review, and their fixes improve the bot.
FIG 09 · Security and compliance
Private by design
Whether a chatbot is compliant depends on how it is deployed. We build it to meet your requirements and document how.
06principles
Data residency
Hosting and model endpoints in US, UK or EU regions, chosen to match your data policy.
PII redaction
Personal data is masked before it reaches a model where it does not need to.
Role-based access
SSO and permission-aware retrieval, so each person only gets answers from content they can see.
UK GDPR and GDPR
Data processing agreements, retention rules and logs, set up for UK and EU users.
HIPAA-aware builds
For US healthcare, deployments designed around HIPAA requirements, on providers that sign the agreements you need.
HealthcareEU AI Act transparency
Users are told clearly that they are talking to AI, with an easy route to a person.
FIG 10 · Measurement
What we measure after launch
Launch is the start. A dashboard shows how the bot performs and what it cannot answer yet, so it keeps getting better.
| Metric | What it tells you | Where it comes from |
|---|---|---|
| Containment rate | Conversations fully handled without a person | Conversation logs |
| Resolution rate | Questions actually answered, not just closed | Follow-up checks and ticket outcomes |
| Handoff rate | How often the bot passes to your team, and why | Handoff events with reasons |
| CSAT | How users rate the answers | Thumbs and short surveys in the chat |
| Cost per conversation | Model and hosting spend per chat | Token and usage logs |
| Top unanswered questions | Gaps in your content to fill next | Questions the bot declined or got wrong |
Targets are agreed with you after the prototype; we don’t promise benchmark numbers before we have seen your data.
FIG 11 · Process · 5 steps
From your content to a trusted bot
A prototype on your own data comes first, then testing with real questions. A fixed written quote covers each phase.
- Step 01
Discovery and content audit
We list the questions that matter, check the content that answers them and agree channels, integrations and success measures. Then a written scope and a fixed quote.
- Step 02
Prototype on your data
A working chatbot on your real content, so you can try it early and see where the gaps are.
- Step 03
Test with real questions
An eval set of real questions scores accuracy, citations and refusals. Hallucination and security tests run before anything goes live.
- Step 04
Integrate and launch
Website, WhatsApp, Slack, Teams or voice, connected to your CRM and helpdesk, with handoff to your team.
- Step 05
Monitor and improve
The dashboard shows containment, CSAT and unanswered questions. We fill gaps, retune and keep the models current.
FIG 12 · What you get
Everything included
Written into your fixed quote, so you know exactly what you are paying for before work starts.
12items
- Question inventory and content audit
- Written scope and fixed quote
- RAG pipeline on your approved content
- Working prototype on your data
- Eval set of real questions and answers
- Hallucination, security and regression tests
- Channel setup: web, WhatsApp, Slack, Teams or voice
- CRM and helpdesk integration with handoff
- PII redaction and role-based access
- Analytics dashboard after launch
- Deployment to your own cloud accounts
- Full source code, prompts and documentation
FIG 13 · Tech & tools
The tools behind the work
Proven, well-supported tools, chosen for your project and set up in accounts your business owns.
- OpenAI
- Anthropic Claude
- Google Gemini
- Llama
- Mistral
- Azure OpenAI
- Amazon Bedrock
- LangChain
- LlamaIndex
- PostgreSQL + pgvector
- Pinecone
- WhatsApp Business API
- Slack
- Microsoft Teams
- Zendesk
- Freshdesk
- Intercom
- HubSpot
- Salesforce
FIG 14 · Who it’s for
Chatbots for every side of the business.
Customer-facing or internal, US or UK, the build follows the same tested process.
3 audiences
Support
Fewer repeat tickets, faster answers.
A support bot that resolves common questions from your help content and hands the rest to your team with context.
- Zendesk, Freshdesk or Intercom handoff
- Answers with citations
- Containment and CSAT on a dashboard
- Website and WhatsApp channels
Sales
Qualify and book while you sleep.
A pre-sales assistant that answers product questions, qualifies visitors and books calls into your calendar.
- CRM sync for every conversation
- Lead scoring rules you control
- Calendar booking
- US and UK time-zone aware
Internal
Your company knowledge, one question away.
An assistant in Slack or Teams that answers HR, IT and policy questions from the documents staff are allowed to see.
- SSO and permission-aware retrieval
- Audit logs
- US, UK or EU data residency
- Private model deployments
FIG 15 · Working with us from the USA and UK
Built in New Delhi. Run on your hours.
Every project gets a point of contact in New York or London and an engineering team in New Delhi. Here is how today’s working days line up, live.
New York
North America
--:--ET
New Delhi team Your working day- Shared working time
- ≈ 3 hours today
- New Delhi is
- 10.5 h ahead
- Live calls, your time
- 9 a.m. to 12 p.m. ET
London
UK & Europe
--:--UK
New Delhi team Your working day- Shared working time
- ≈ 4.5 hours today
- New Delhi is
- 5.5 h ahead
- Live calls, your time
- 9 a.m. to 1:30 p.m. UK
Three ways to work together
- 01
Fixed-scope project
A written scope, one fixed price and a dated plan. Suits websites, apps and MVPs.
- 02
Dedicated team
Designers and engineers on your roadmap every month, billed monthly.
- 03
White label
For US and UK agencies: our work, your brand, unbranded deliverables.
Every engagement
- Fixed quote in USD, GBP or INR after a free 30-minute call
- NDA before discovery. You own all code, designs and content
- A working demo every sprint, not status slides
- Reply within one business day, calls inside your hours
Book a call
Calls on ET or UK hours
FIG 16 · Compare
Custom chatbot or off-the-shelf?
| Custom build (Elgrith) | Intercom Fin or Zendesk AI | Microsoft Copilot Studio | |
|---|---|---|---|
| Best for | Unusual data, many systems, or a bot inside your own product | Support teams already on Intercom or Zendesk | Microsoft 365 organizations building internal bots |
| Data control | Your cloud, your model choice, your retention rules | Vendor-hosted, within their settings | Inside your Microsoft tenant |
| Integrations | Any API, database or channel | Strongest inside their own helpdesk | Strongest with Microsoft apps |
| Effort to launch | Discovery, build and testing | Fast on existing help content | Low-code setup; custom work for complex flows |
| Running costs | Model usage plus hosting | Vendor subscription and usage fees | Vendor licensing and usage fees |
| Lock-in | None: you own the code and prompts | Tied to the helpdesk | Tied to Microsoft |
FAQ
Frequently asked questions
Straight answers about AI Chatbot Development with Elgrith.
It depends on scope. The main cost drivers are the number of content sources and channels, the integrations with your CRM or helpdesk, your security requirements, the depth of testing, and the running cost of model tokens. After a free call you get a written scope and one fixed quote. We also estimate the running cost per conversation before you commit.
FIG 17 · Related
Keep exploring
Free 30-minute call
Turn your content into answers people trust.
Send us the questions your team answers every day. After a free call you get a written scope and a fixed quote for your chatbot.
Pick a day for your call
OpenPick a day. You'll choose a time in your own time zone on the next step.