Customer support assistants
Answering from your documented policies and live account data, with confident handover to a human when confidence drops.
AI Chatbots & Automation
AI assistants that answer correctly or hand over
Turn repetitive conversations into automated customer experiences.
We build AI chatbots and internal assistants grounded in your own documentation and systems — so they answer from your policies rather than inventing something plausible.
- Fixed scope & price
- Agreed before any code is written
- You own everything
- Code, infrastructure, and documentation
- Europe & MENA
- Overlapping hours, async written updates
The problem
Generic chatbots make things worse
A bot bolted onto the site answers three questions badly, cannot see any real customer data, and has no way to escalate. Customers learn to type 'agent' immediately, and the deflection rate the vendor promised never materialises.
- Support answers the same twenty questions every day
- The existing bot cannot access order, account, or booking data
- There is no clean handover, so customers repeat themselves to a human
- Staff waste hours searching internal documentation
- Leadership is nervous about an AI saying something wrong publicly
What we build
What we actually build
Assistants grounded in retrieval over your own content, connected to the systems that hold the answer, with explicit boundaries on what they are allowed to say and clear escalation when they hit them.
Sales & qualification assistants
Answering product questions, qualifying against your criteria, and booking meetings straight into the calendar.
Internal knowledge copilots
Private assistants over contracts, procedures, and wikis — respecting the permissions each employee already has.
Automation agents
Assistants that take action in your systems — creating tickets, updating records, triggering workflows — not just producing text.
Capabilities
What is included as standard
- Retrieval-augmented generation over your content
- Grounded answers with source citations
- Escalation and human handover rules
- Tool use against your live systems
- Permission-aware retrieval
- Guardrails and refusal boundaries
- Multi-language conversations
- Conversation analytics and quality review
When companies call us
Typical situations we are brought into
Support volume is scaling with headcount
Ticket volume rises with growth, most of it repetitive, and hiring is the only lever you currently have.
Your knowledge is unfindable
The answer exists in a document somewhere, but staff cannot locate it fast enough to be useful on a live call.
Leads arrive outside working hours
Enquiries land at night or across timezones and go cold before someone replies the next morning.
A previous chatbot failed
You tried one, it embarrassed you or achieved nothing, and you need a version grounded in real data with real limits.
Technology
The stack we build on
Models
- Claude
- GPT-4
- Open-weight models
- Embeddings
Retrieval
- Vector databases
- Hybrid search
- Re-ranking
- Chunking
Application
- Node.js
- Python
- Streaming APIs
- Tool calling
Operations
- Evaluation suites
- Tracing
- Cost controls
- Audit logs
Process
How the engagement runs
- 01
Discovery & scope
We map your current systems, constraints, and commercial goals, then agree what is in scope — and what deliberately is not.
- 02
Architecture & plan
You get a technical approach, milestone plan, and fixed commercial terms before any code is written.
- 03
Build in increments
Two-week increments with working software at the end of each. You review real builds, not status decks.
- 04
Launch & handover
Testing, migration, and documented handover so your team can operate the system without depending on us.
- 05
Ongoing partnership
Support, iteration, and a named engineer who already knows your stack when the next thing comes up.
Integrations
Tools we connect to regularly
Not an exhaustive list — if it exposes an API, we have probably worked with something like it.
ZendeskIntercomHubSpotSalesforceSlackMicrosoft TeamsNotionSharePoint
Questions
What buyers usually ask
The assistant answers from retrieved passages of your own content rather than model memory, cites what it used, and is instructed to say it does not know and escalate when retrieval returns nothing relevant. We test this with an evaluation set before launch and monitor it after.
Clients
What working with us is like
Leet Force didn't just build us a product — they transformed our entire digital presence. The attention to detail is unmatched. Every interaction feels premium.
Ayesha Nadeem
CEO, Rawal Capital
Our new site won Site of the Day on Awwwards within weeks of launch. Leet Force understands what 'premium' actually means.
Bilal Ahmed
Founder, Margalla Creative
They navigated complex healthcare requirements with ease while delivering a beautiful, intuitive platform our patients love.
Dr. Sana Qureshi
Chief Medical Officer, Chenab Health
Related services
What usually comes with this
Bring us your twenty most repeated questions
That list tells us quickly whether an assistant would genuinely help, and roughly what it would deflect. If the answer is no, we will say so.