AI Agents & Chatbots
Support agents that actually answer the question
We build AI chatbots and autonomous agents that read your real documentation, resolve customer queries around the clock, and hand off to a human the moment it matters.
Talk to usCustomer support that scales without scaling headcount
Most chatbots fail because they guess. They were trained on generic data, they hallucinate policies you never wrote, and they frustrate customers into demanding a human anyway. The damage is real: every wrong answer erodes trust, every dead-end conversation pushes someone toward a competitor, and every escalation that should never have happened costs your team time they did not have to spare. A chatbot that cannot be trusted is worse than no chatbot at all, because it trains your customers to skip the bot entirely.
An AI agent grounded in your own knowledge behaves differently. Before it replies, it retrieves the exact answer from your help center, product docs, policies, and past tickets, so every response reflects what your business actually says — not what a model imagined. When the answer is not in your knowledge base, it does not invent one; it says so plainly and routes the customer to a person. That single design decision is the difference between a tool your customers learn to rely on and one they learn to avoid.
Techies designs, builds, and operates AI agents that automate the repetitive 70 percent of support so your team can focus on the cases that need judgment. We use retrieval-augmented generation (RAG) over your company knowledge, connect the agent to the channels your customers already use, and serve them fluently in both Arabic and English. The agent answers instantly, escalates cleanly with full context, and gets measurably better every week as we close the gaps real conversations expose. You keep one accountable team owning the whole stack, from the retrieval pipeline to the analytics dashboard.
How we build an agent you can trust
We start with your content, not a generic template. In a short discovery we inventory the knowledge the agent will rely on — help articles, PDFs, internal wikis, product specs, and the ticket history that captures how your team really answers questions. We clean and structure that material, chunk it sensibly, and build the retrieval pipeline that lets the agent find the right passage in milliseconds. Garbage in is garbage out with AI more than anywhere else, so the quality of this groundwork sets the ceiling on everything that follows.
Next we shape behaviour. We write the system instructions that define the agent's tone, its boundaries, and exactly when it should stop trying and hand off to a human. We connect it to the tools it needs to be useful rather than merely conversational — your helpdesk to create and read tickets, your CRM to recognise a returning customer, your order system to answer "where is my package" with a real tracking number. An agent that can only talk is a deflection that annoys; an agent that can act resolves the ticket end to end.
Finally we measure and tune. Before launch we run the agent against a test set of real historical questions and score its answers for accuracy and safety, so you ship with evidence rather than hope. After launch the work continues: every conversation is logged, every unanswered question is surfaced, and a weekly tuning loop turns those gaps into new knowledge and sharper instructions. The agent you launch is the worst version you will ever run — it improves with every week of real traffic.
What our AI agents cover
RAG over your knowledge base
The agent retrieves answers from your real docs, FAQs, policies, and ticket history before responding, so it grounds every reply in your content instead of guessing. We build the embedding and vector-search pipeline that finds the right passage fast, and we keep it in sync as your knowledge changes. The result is answers that match what your business actually says, today.
Multichannel deployment
One agent, many surfaces — your website, WhatsApp, Messenger, email, and in-app widgets all share the same brain and the same answers. Customers get a consistent experience wherever they reach you, and you maintain one source of truth instead of a different bot per channel. Adding a new channel later is a configuration step, not a rebuild.
Arabic & English fluency
Native handling of Modern Standard Arabic and English in the same conversation, including dialect-aware understanding and correct right-to-left rendering. The agent can read a question in Arabic and answer in Arabic, switch to English mid-thread, or handle the mixed Arabizi that real customers actually type. Bilingual support stops being a separate team and becomes a default.
Tool use and real actions
Beyond answering, the agent takes action through your existing systems — looking up an order, resetting a password, creating or updating a ticket, or checking subscription status. We connect it to your helpdesk, CRM, and internal APIs so it resolves the request rather than just describing how. This is the line between a chatbot that deflects and an agent that actually helps.
Human handoff with context
When a query needs a person, the agent escalates to your team with the full transcript and a short summary, so no customer ever repeats themselves. Routing rules send each case to the right queue or specialist, and the agent flags urgency and sentiment so high-risk conversations jump the line. The handoff feels seamless to the customer and saves your agents the first five minutes of every ticket.
Analytics & continuous tuning
Dashboards on deflection rate, resolution time, satisfaction, and unanswered questions give you a live view of how the agent performs. Those same signals feed a tuning loop that closes knowledge gaps every week, so the agent keeps getting better instead of quietly drifting. You always know what the agent is handling, what it is missing, and where the next improvement should go.
Guardrails and brand safety
We configure input and output filtering, prompt-injection defenses, and policy checks so the agent stays on-topic, on-brand, and out of trouble. It declines requests outside its remit, refuses to be talked into off-brand or unsafe responses, and never exposes data a customer should not see. You decide the boundaries; the guardrails enforce them on every single conversation.
Privacy and access control
The agent only retrieves what each user is allowed to see, and sensitive data is handled according to your policies and local regulations. We log events for audit without logging secrets, and we keep customer data inside the boundaries you define. Automating support never means loosening the controls that protect your customers.
Frequently asked questions
- Will the chatbot make things up?
- Not when it is built on retrieval. Our agents answer from your approved sources and are configured to say they do not know and hand off, rather than invent an answer, when the knowledge base has no match. We back this with an evaluation set of real questions that we score before launch, so you have evidence of how the agent behaves rather than a promise. Grounding the model in your content and giving it permission to defer is what keeps it honest.
- Can it really handle Arabic and English well?
- Yes. Modern large language models like Claude handle Arabic and English natively, and we tune the agent on your terminology so it understands questions and replies correctly in either language, even when a customer mixes both in one message. It manages Modern Standard Arabic, common dialects, and the Latin-script Arabizi people actually type, with correct right-to-left rendering throughout. Bilingual support that used to need two teams runs on one agent.
- How does it connect to our existing tools?
- We integrate with your helpdesk, CRM, and channels through their APIs. The agent can read order status, look up an account, create and update tickets, and escalate inside the tools your team already lives in, so nothing moves to a separate silo. We map exactly which actions it is allowed to take and with what permissions during the build. If a system you use has an API, we can almost always connect to it.
- What happens when it cannot answer?
- It hands off to a human with the full conversation and a short summary, routed to the right queue based on rules you define, so the customer never starts over. It also logs the unanswered question so we can add the missing knowledge in the next tuning cycle, which means the same gap rarely happens twice. Over time the handoff rate falls as the knowledge base learns from real traffic.
- How long does it take to launch?
- A focused first agent over a well-organised knowledge base typically goes live in a few weeks, and we aim to put a working version in front of you early rather than after months of silence. The timeline depends mostly on the state of your content and the number of integrations you need on day one. We launch with a contained scope, prove it on real traffic, then expand channels and capabilities from there.
- Will it replace our support team?
- No — it changes what your team spends time on. The agent absorbs the high-volume, repetitive questions that burn out good people, freeing your specialists to handle the complex, sensitive, and high-value cases where human judgment genuinely matters. Most teams use the freed capacity to respond faster and offer support they could never staff before, rather than to cut headcount. The goal is leverage, not replacement.
- How do you keep customer data safe?
- The agent only retrieves what a given user is permitted to see, sensitive data is handled according to your policies and local regulations, and we log events for audit without logging secrets or full personal data. Access to systems is scoped to the minimum the agent needs, and the guardrails block attempts to extract data through clever prompting. Security is part of the design from the first week, not a checkbox at the end.
- How do you measure whether it is working?
- We track deflection rate, resolution time, customer satisfaction, and the volume of questions the agent could not answer, and we put all of it on a dashboard you can see at any time. Those numbers tell you the business impact and also point directly at where the next improvement should go. Because we tune weekly against real conversations, the trend line should move in the right direction month over month.
- Can it handle our specific products and policies?
- Yes — that is the entire point of grounding it in your own knowledge. The agent answers from your product docs, pricing, and policies rather than generic internet data, so it speaks in your terms about your offering. When your products or policies change, we update the knowledge base and the agent reflects the change immediately, with no retraining required. The more specific your content, the more useful the agent becomes.
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