Your product documentation
Buyers configuring a script they bought
A buyer with no developer asks how to point the app at their own domain. The agent finds that step in the deployment guide and answers with it, rather than linking to the whole page.
AI customer support automation
Your team knows the answer. They have typed it nine times today.
Most support tickets are a question somebody already answered. An agent that can read your documentation and your closed tickets answers it again, in the words your team would use.
- Answers only from your own docs
- Escalates rather than guesses
A questionFrom your customer
Your documentationSearched by meaning
Closed ticketsHow you answered before
The answerBuilt from what it found
RepliedIn your own words
Passed to a personWith the context
What RAG powered support is
AI customer support automation uses retrieval augmented generation, which means the model is given your own material to answer from rather than answering from memory. Your documentation and your closed tickets are indexed so they can be searched by meaning. The agent finds the passage that applies and answers from it, then hands over anything it cannot find.
The same twenty questions, forever
Support volume rises with customers, and most of that rise is the same handful of questions. The hard tickets are the ones worth a person, and they sit in a queue behind password resets. Your best support person spends the morning on questions your own documentation already answers in full.
- 01
Tier one eats the day
Billing questions arrive faster than anybody clears them. The interesting tickets wait behind them.
- 02
The answer already exists
It is in the documentation, or in a ticket. Nobody finds either one under time pressure.
- 03
The old bot made it worse
A decision tree that never had the answer taught your customers to hunt for the button that reaches a person.
How we build support agents that work
- 01
Your knowledge, indexed
Documentation and closed tickets are chunked, then embedded into a vector database your team controls. Search then runs on meaning rather than on the words a customer happened to type.
- 02
Wherever your customers already are
The agent sits in the help desk your team already answers in, reached through its API. Your customers never learn a new place to ask.
- 03
A handover that carries context
Anything outside the documentation goes to a person. What the customer asked and what the agent found travel with it, so nobody starts again.
How the first three weeks run
- Week 1
01We read what you already have
Two days with your team, and a look at the tickets you closed last quarter. The repeat questions sort themselves into a list.
- End of week 2
02You get a costed plan
The plan says which questions an agent should take first, and what that clears off the queue. You decide whether it goes ahead.
- From week 3
03It goes live on a narrow set
The agent starts on the questions it answers best. The set widens as the answers hold up.
An old chatbot against a RAG agent
Most buyers have been sold the first one already. What separates them is what the thing is allowed to answer from in the first place.
| Measure | A scripted bot | A RAG agent |
|---|---|---|
| How it finds an answer | A decision tree somebody drew | Searches your documents by meaning |
| What it is built from | Conversation flows written by hand | The documentation you already have |
| What it gives back | A link to a help article | The passage that answers the question |
| When the docs change | Somebody rewrites the flow | The index is rebuilt and it follows |
| When it does not know | Guesses, or loops | Says so, and fetches a person |
Support automation in practice
Three places where the questions repeat. In each of them the agent is reading something the business had already written down.
Your app's help panel
Billing questions inside a ledger app
Somebody asks why an expense split the way it did. The agent explains the rule from your own documentation, and the engineering team never sees the ticket at all.
Your community platform
Permissions and setup on a live video app
A user cannot get their microphone working. The agent walks them through the permission their device is asking for, inside the app, while they wait.
What the agent is allowed to say
The boundary is the whole point of this architecture. An agent that can only answer from your own material is an agent that cannot invent a refund policy.
- Answers from your material only
- If it is not in your documentation or your tickets, it is not an answer.
- Escalates instead of guessing
- Not knowing is a routing decision rather than a failure.
- Every answer is traceable
- You can see which passage an answer came from.
What the support agent is built from
We fit the agent around the help desk you run. Nothing on this list is a requirement, and the work goes ahead against whatever your software was built on.
- The models that answer
- ClaudeAnswering from your own materialGPTDrafting and classificationEmbeddingsTurning your docs into search
- Where your knowledge sits
- pgvectorYour documents, made searchablePostgreSQLTickets and reportingRedisQueues and rate limits
- How it reaches your desk
- MCPOne way into your systemsPythonIndexing and evaluationn8nTriggers and routing
What people sayNot our words.
Not our words.
Theirs.
Every quote here is a real Trustpilot review. We did choose which ones to show you. The score beside them is the part we do not control, and it counts all 29 reviews.
Trustpilot4.4out of 5Excellent29 reviews · checked 19 August 2026Read all of them
These reviews are for Appkodes, our software product division.
A Joysale client on the product and the service
He runs a marketplace built on Joysale, our Letgo style product. The clip is his own account of working with us.
A Fantacy client on the build
Fantacy is our Amazon style retail product. He goes through what was built and how the work ran.
An Airfinch client, filmed after his written review
Airfinch is our Airbnb style rentals product. He had already left the same review on GoodFirms before recording this.
A second Joysale client on the same product
Another marketplace running on Joysale. Worth watching beside the first, since the two bought the same thing.
Trustpilot
I've worked with Appkodes for 7 years on 4 different projects. We constantly require support or the implementation of new features, and we have the guarantee that the quality of their work remains the same throughout this time.
Juan VásquezSep 2025Trustpilot
Appkodes exceeded all of our expectations! From the very first contact, the team demonstrated a high level of professionalism, technical expertise, and commitment to quality.
Global SoftwinMay 2025Trustpilot
Appkodes team helped me to launch my healthcare application very quickly. Their software was very close to my requirements and adding some extra features made my project easy.
WassimApr 2025Trustpilot
I so much love your services and I will continue to patronize your company.
Kolawole Alaba JohnsonApr 2025Trustpilot
I worked with AppKodes for a website and mobile app development project, and overall, I'm very satisfied with the results. Their team was responsive and flexible throughout the process, and they delivered a product that met my expectations both in design and functionality.
Яша ФирузApr 2025Trustpilot
It was a good experience working with the team. They understood my ideas clearly and built everything as expected. The team was supportive, quick to respond, and helped me whenever I needed changes. Thank you for your hard work and support!
Prem SharmaApr 2025Trustpilot
I have got a mobile app project going on successfully with the team. Their Support is good. turn around time for any requirement is great. Every detail of my app is meticulously designed. THANK YOU APPKODES.
Fast Fiber NetworksApr 2025Trustpilot
Appkodes is a leader in developing high-quality applications and websites. It was a pleasure working with them, and this certainly won’t be our last collaboration. My experience was exceptional, they developed an outstanding app and website, with smooth and refined interactions.
BaderApr 2025Trustpilot
Overall very good experience. I have been availing services for past 3 years. They are available for discussions and resolving issues whenever we faced any. Mr. Saravana has been looking after our project and I'm very much happy with his timely response. I would definetely recommend.
Vannala RajuApr 2025Trustpilot
Initially, I was hesitant to deal with them, believing their customer service would be poor. However, I was surprised. They act with great responsibility and professional efficiency. My regards to them.
Ahmed NhariApr 2024Trustpilot
You have been supporting me very quickly in every matter, especially in the last 2 months, and this makes me very happy.
Deniz SeçerJan 2024Trustpilot
Very professional. Our project was quite complex and they covered all the aspects. Appkodes did an amazing and professional job developing and creating our Apple and Android apps. I was positively impressed with the communication you can absolutely trust on what they say.
Anu JosephJul 2023Trustpilot
Mani and Saravanan of the Appkodes team are amazing, they have done the best to create and support my project! I give them 10/10 stars for their efforts and work!
Joely CineasJul 2023Trustpilot
It was really great, they are there for me whenever I had a problem or to fix something. Thank you so much Ameer
GomezApr 2023Trustpilot
I've been working with Appkodes for almost a year and i can recommend them to work with as they are so much friendly and professional and you can clearly see it once you start your project right away. They are intact and they are transparent with their communication.
JohnFeb 2023Trustpilot
I have to be honest, sometimes it's hard to find a company or someone abroad to do your project. Not only might you waste your time and money, there is this thing called trust. In business you must trust the person you are dealing with.
Zack GizawDec 202216 of 29 reviews, plus 4 videos
Businesses we have built for
Frequently asked questions
Can the AI use our existing ticket history?
It is usually the most valuable thing you have. Closed tickets are cleaned, structured and indexed, which teaches the agent how your team actually phrases an answer and how the awkward cases were settled. Whatever help desk you run, the work is the same as long as it has an API to export from.
Will the AI make things up or hallucinate?
It is confined to your own material. Retrieval augmented generation hands the model the passages that matched and tells it to answer from those. An answer that is not somewhere in your documentation is not one that it can give. Where nothing matches, it escalates rather than filling the gap.
Does it handle customers writing in other languages?
Yes. The model reads a question in whatever language it arrives in and answers in that same language. Your documentation only had to be written once. Test it on your own material first.
What is RAG chatbot integration?
It puts a retrieval step in front of the model. The customer's question searches your indexed documents first, and only the passages that come back are given to the model to answer from. That one retrieval step is the whole difference between a support agent and an ordinary chatbot.
Do you do automated ticketing system setup as well?
Yes, and it is usually the same project. Routing rules, priorities and the question of what an agent may close all get decided in week two. An agent answering well into a queue nobody has organised does not help very much.
How is this different from custom AI chatbot development?
A chatbot is judged on the conversation, and this one is judged on whether the ticket closed. Most of the build is not the chat window. It is getting your documentation and your ticket history into a shape the model can search.
Next stepLet AI do the repetitive
Let AI do the repetitive
half of the job.
Data entry, answering the same tickets, chasing numbers between systems. We automate the parts that repeat. Your team keeps the parts that need judgement.
