Chatbots for leads and qualification
Capturing enquiries, filtering contacts, routing and first answers aimed at conversion.
AI automation and chatbots
Automation that takes off your team the work it repeats every day
We design AI automation, chatbots and intelligent workflows as business tools: integrations, data, human fallback and control. For companies, SMEs, startups and teams who want more efficiency without new chaos.
- Workflows across email, CRM, support, documents and existing systems
- AI chatbots for lead generation, support and the internal knowledge base
- Assistants for sales, back office and customer care
- Guardrails, logging, human handoff and metrics, so the system stays governable
AI, integrations, orchestration, knowledge base and supervision in the same operational flow.
The problem
Where the repetitive manual work piles up.
A lot of AI projects start as isolated experiments, or as chatbots disconnected from how the company actually runs. The result is an interesting demo, little real impact and a new bottleneck.
Repetitive tasks still handled by hand across email, sheets and separate tools
Information scattered so widely the team looks up the same answers over and over
Leads, enquiries or tickets slowed by manual, unclear handovers
Chatbots that answer badly because they have no data, no rules and no fallback
Fragile automation that breaks the moment a process or an input changes
Decisions made without measuring time saved, quality or completion rate
The usual outcome: more tools, more complexity and barely any difference to time, quality or operating cost.
How we approach it
Less manual work, with control over cost and quality.
First we find where the time goes, where the flow stalls and which decision needs to move faster.
Only then do we choose the model, the integrations and the level of autonomy you can actually sustain.
Only then do we choose the model, the integrations and the level of autonomy you can actually sustain.
Mapping the processes, the bottlenecks and the outcome you want
Settling data, sources, rules, permissions and checkpoints
Choosing automation, chatbots or assistants to fit the operation
Integration with CRM, ticketing, documents, email, Slack or internal systems
Human fallback, logging, security and exception handling
A progressive rollout with clear use cases and shared metrics
Continuous work on time, quality and completion rate
What we can build
What we build
Customer support assistants
Answers from the knowledge base, request status, operational FAQs and handover to a person when it is needed.
Document automation
Reading, extracting and routing data from PDFs, forms, email or attachments.
Workflows across systems
Automatic handovers between CRM, ticketing, e-commerce, calendar, ERP or internal tools.
Internal copilots
Contextual assistants for sales, operations, support or back office.
AI pipelines with rules and supervision
Task orchestration, checks and human handoff for the processes that carry weight.
Technology and stack
Technology and architecture
Every technical choice is made against answer quality, integration with your systems, cost control and how easily it can change.
LLM orchestration
Models and prompt flows selected on accuracy, cost, speed and operational risk.
n8n / Make / custom workflows
Quick automation or a sturdier pipeline, depending on how complex the process is.
RAG and knowledge base
Contextual retrieval, so chatbots and assistants answer from something real.
CRM / ticketing / email / Slack
The AI works where the team already works, instead of becoming a tool nobody opens.
Guardrails and human handoff
Checks, limits and escalation to a person, to cut errors and keep the thing dependable.
Logging and analytics
Outcomes, errors, timings and impact watched, so the system improves over time.
Permissions and security
Access control, approved sources and data protection that match the company context.
Deployment and maintenance
Orderly releases, observability and controlled changes as the process evolves.
What we measure
We track what actually counts: time saved, automation rate, answer quality and the effect on the critical handovers.
Time saved per task
Automation rate
Answer quality
Effect on leads or operations
OpenAIn8nMakeRAGVector DBWebhookCRMSlackPythonFlutterKotlinCoroutines
How the work runs
How we work
01
Process analysis
The goal, the blockages, the data involved and the risk thresholds.
02
Flow design
Inputs, decisions, outputs, exceptions and where a person takes over.
03
Build and integrations
Models, systems, knowledge base and automation joined into one coherent flow.
04
Testing and guardrails
Real cases, failures, fallbacks, answer quality and the limits of the system.
05
Rollout and tuning
Progressive release, monitoring and continuous refinement against real data.
On time and quality
Results you can measure
The result is not a chatbot on your website: it is less friction, faster handovers and people and systems working better together.
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Projects shipped
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Services running
Who it is for
Who it is for
We work well when the project has to remove manual work, improve the quality of the flow and stay governable after release.
A good fit if…
You have repetitive processes, frequent requests or bottlenecks that can be automated.
You want a partner who brings AI, integrations, operational rules and supervision together.
You want a system the team still uses six months after release.
Not a good fit if…
You want AI for appearances, with no concrete use case.
You want a generic chatbot with no data, no process and no human fallback.
You have no interest in measuring time saved, quality or completion rate.
You would rather have a quick demo, even a fragile one nobody can maintain.
AI automation and chatbots work when the process, the data, the limits and the supervision are designed together.
FAQ
Common questions
Where should an AI automation project start?
With the process that has the most friction or repetition. On the call we pick the use case with the fastest payoff.
Chatbot, workflow automation or internal assistant?
It depends on the problem: support, leads, documents, operations and sales all call for different answers. The shape follows the real process.
Can you integrate AI with the systems we already use?
Yes. We can connect CRM, ticketing, email, databases, documents, Slack and internal tools, keeping the checks and fallbacks where they are needed.
How do you handle errors, hallucinations or out-of-scope questions?
With guardrails, a controlled knowledge base, logging, confidence thresholds and human handoff on the cases that should never be handled alone.
Do our data need to be in perfect order first?
Not always. In most cases we start from a realistic scope, organise the sources that matter most and build the system up progressively.
Let us talk about your next project
Tell us the goal and the context. We answer with a first assessment and the next steps, no strings attached.
Would you rather talk directly?