Order tracking, booking an appointment, a question about an invoice, a change of address: every day, a large share of the requests reaching your customer service look alike. We design an AI agent that answers them around the clock, on your website, by email or on WhatsApp. It checks your tools to give the right information, carries out simple tasks, and hands over to your customer service agents, with full context, the requests that deserve human attention.
265+ projects delivered in 35 countries · 4.9/5 average rating on Clutch · 20+ AI solutions deployed
Do these situations sound familiar?
Agents answering “Where is my order?” ten times a day
Requests sent on Friday evening that wait until Monday morning for an answer
Peaks in activity, during sales, back-to-school or year-end closing, absorbed through overtime
A chatbot installed a few years ago, which your customers have learned to bypass by typing “agent” in their very first message
Information scattered across the CRM, the billing tool and the inbox, which each agent has to pull together before answering
Your customers want a quick answer, but not at any price. 90% of French people would rather wait longer to talk to a human agent than be handled by a virtual one, and chatbots remain the least appreciated contact channel, with only 50% of customers satisfied[1]. A successful AI agent therefore handles quickly what can be handled, and leaves your teams the time to take good care of the rest.
Terms and conditions, catalog, procedures, FAQs: the agent relies on your content, and only on it, to answer accurately.
Instead of explaining what to do, the agent does it: it checks the customer’s file and carries out the actions you have authorized.
Reference: SmartCab, a taxi service in Geneva where customers book their ride with a simple WhatsApp message, the AI handling everything from booking to billing.
A question outside its scope, an unhappy customer, an explicit request to talk to someone: the agent passes the conversation to the right person, without the customer having to repeat everything.
Even when it doesn’t answer itself, the agent saves your teams time and helps you understand what drives your customers to contact you.
No need to ask your customers to change their habits: the agent sits where they already write to you or call you.
| Channel | What the agent does | Good to know |
|---|---|---|
| Website chat | Answers live, guides the customer and opens a ticket if needed | The simplest channel to start with |
| Email and forms | Sorts messages, answers common requests and drafts a reply for the others | Ideal for absorbing volume peaks |
| WhatsApp and messaging apps | Talks with the customer as a human agent would, from the question through to the booking | Very popular with customers who don’t want to install an app |
| Phone | Picks up, understands the spoken request and handles or transfers the call | Requires special care with accents and transfers |
Most support software now offers its own AI agent. They suit some needs very well, others less so. Here is how we help you decide.
| Agent built into your support software | Custom agent designed by Kreante | |
|---|---|---|
| Setup | Fast, if all your data is already in that software | A few weeks, with a testing phase on your real requests |
| Possible actions | Limited to the tools compatible with that software | In your own tools: ERP, business software, calendar, billing |
| Business rules | Standard configuration | Adapted to your procedures and your exceptions |
| Cost | License and usage-based billing, which grow with volume | Development budget, then the running cost of the AI models |
| Ideal for | Simple requests, in an already centralized environment | Requests that involve several tools or rules specific to your business |
We recommend the off-the-shelf solution when it is enough, and build a custom agent when your business warrants it.
An AI agent speaks on behalf of your company. Its mistakes are binding on you: in 2024, Air Canada was ordered to compensate a customer whose chatbot had promised a refund its fare rules did not provide for[2]. An agent open to the public must also resist manipulation attempts, such as a message crafted to make it grant a goodwill gesture or reveal another customer’s information.
Agents assembled in a few hours with AI tools, then put online without checks, are particularly exposed, especially since attackers also use AI to spot these flaws.
At Kreante, every agent is designed and tested to stay in its role:
Answers limited to your information; when in doubt, the agent hands over rather than improvising
Access restricted to the data of the customer in the conversation, after identity verification
Actions governed by clear limits, such as a maximum refund amount
Manipulation attempts tested before launch, then monitored
Your customers’ data protected and never used to train the models
Customers informed that they are interacting with an AI, in line with regulations
Before writing a single line of code, we analyze past conversations with your customers to identify the most frequent requests and those that should stay in your agents’ hands.
The agent connects to your CRM, your support software and your business tools. Your teams keep working in their usual environment.
Complaints, sensitive situations, long-standing customers: we help you define what the agent should not handle, as much as what it can take on.
Share of requests resolved without handover, response time, post-conversation satisfaction: you quickly know what the agent brings, and where to improve it.
The code, the instructions and the knowledge base are yours. You can switch AI model providers without rebuilding everything.
Free
30 minutes with an expert
Custom quote
Budget approved before we start
Custom quote, based on scope
Budget and scope approved together in writing
We study your past conversations to identify recurring contact reasons, the tools involved and the cases to keep for your agents.
We gather, update and organize the documents the agent will rely on.
The agent is tested on real past requests before going live. On the development side, our AI tools write the code, our senior developers steer and approve it.
One channel, a few requests and limited actions at first, under your teams’ watch.
New contact reasons, new channels, new actions, added as results come in.
Hands-on sessions so your teams can work confidently alongside the agent, and know how to improve it.
Payment reminders, email sorting, document analysis: other AI solutions can extend your agent’s work.
Challenge
Stack
Performance and payroll management platform for AutoCartel field photographers.
Challenge
The platform ingests property data daily via Zillow scraping, runs AI-driven renovation cost and ARV estimates using OpenAI, and surfaces the highest-potential deals first. Users can review…
Stack
An AI-powered real estate intelligence platform built for a Miami-based investment team. DAVCO AI replaces manual Zillow filtering and spreadsheet-based calculations with an automated map interface that displays estimated profit margins across all active single-family listings in the Miami area.
Challenge
Tango event organizers across Europe were running everything manually — registrations, confirmations, payments, check-in. They needed one purpose-built platform to manage the full event lifecycle,…
Stack
TheFlow is a web platform built for tango event organizers in Europe. Kreante evolved it across multiple phases from a basic registration tool into a complete event management and ticketing product — covering event creation, participant management, waitlists, online payments, QR check-in, automatic invoicing, and an international tango event calendar.
Challenge
Kreante developed a comprehensive platform for Pure Engagement using NoCode technologies. Built with Bubble for the frontend and Xano for the backend, this solution facilitates organizational…
Stack
Pure Engagement needed a platform capable of handling the complexity of organizational transformation, recognizing that success depends not only on structural change but also on people’s psychological and emotional transition.
Challenge
Build an iOS app that turns iPhones plus an audio interface into a complete, professional podcast recording studio, capturing high-quality sound and video across several phones at once and keeping…
Stack
A mobile app that lets creators record, sync, edit, and export podcast audio and video using a dedicated interface and multiple iPhones working together as one studio.
Challenge
Patients leaving clinic checkups with a list of medical recommendations and lab results often had no clear, practical way to turn that information into daily meals, leading to poor adherence and high…
Stack
Kreante built REMI AI, a system that reads a patient's genetic and medical test results and automatically turns them into a personalized nutrition and supplement plan that gradually evolves over several months, with clinic staff reviewing every AI-generated interpretation before it reaches the patient.
Challenge
Stack
In the evolving landscape of web development, choosing the right approach for custom software development is crucial.
Challenge
Stack
In the sustainability-focused retail landscape, product repair and maintenance play a pivotal role in circular economy initiatives. Businesses are increasingly adopting innovative solutions to reduce waste and extend product life cycles.
Challenge
Stack
When Garde-Robe presented their innovative vision to make fashion more social and collaborative, Kreante, a leading LowCode agency, eagerly embraced the challenge.
Challenge
When INSPO approached our LowCode agency with their vision of creating the definitive platform for thought leadership, we knew this project would push the boundaries of what’s possible with…
Stack
In the rapidly evolving landscape of LowCode development, creating sophisticated applications no longer requires months of traditional coding.
Challenge
Stack
Connect with verified construction professionals, find new projects, recruit subcontractors, and grow your business with ShareLeads' trusted B2B platform.
Challenge
The basketball community in Washington D.C. lived on courts and in scattered WhatsApp groups. What was missing: a place to give it visibility, bring more people together, find players at your…
Stack
What we built In 3 months, Kreante delivered all three platforms at once. The mobile app lets you find pickup games within a 10-mile radius, rate players to compete at the right level, track your progress, and meet up to watch games together. Two tiers: a free version and a premium subscription at $39.99/season — proof that the community is willing to pay to play better. For this kind of project, visual identity isn't just a detail — it's what creates the sense of belonging from the very first open. The entire branding was conceived and built by Kreante. The landing page was built to convert: a strong visual world, a clear message, one goal — trigger the download. The e-commerce store pushed the logic even further: unapologetic street style, rooted in DC culture, to rep your colors beyond the court. Launched at a Virginia tournament, HoopSquad is now live across 13 regions in the United States — on the App Store and Google Play.
Challenge
The Meetern team had been connecting students and companies for years, through physical events. Many great encounters and opportunities later, they understood that to create real impact at scale,…
Stack
What we built Kreante designed and developed Meetern: a complete matchmaking platform, with three distinct interfaces for students, companies, and academic institutions. Students build their profile, apply, and track their applications. Companies post opportunities and receive intelligently matched profiles. Academic institutions monitor placements in real time. Across all three: integrated messaging and a matching algorithm that replaces manual introductions. The platform is multilingual, French and English at launch, Dutch on the way. A V1 delivered in 6 months, a V2 launched in March 2026 with extended language support. Today, 50 to 100 active users every day. And a team that no longer runs events, but a platform.
Challenge
Every manager knows a motivated team performs better. But motivation is invisible. And without understanding what truly motivates each person, engagement initiatives remain educated…
Stack
Kreante designed and developed Motives Solutions: a bilingual SaaS platform (FR/EN), from branding to application. Team members answer 3 anonymous questions. The app analyzes responses and generates a detailed report by motivational driver, for each individual, each team, each organization. Two modules: Motives TEAM for team-level insights, Motives ORGA for the full picture. Tracking is longitudinal: engagement evolution over time, visualized. Three questions. A clear picture of what truly moves a team forward. Measuring the invisible, so you can finally act on it.
Challenge
After a decade training thousands of women for tech jobs, Laboratoria saw its graduates stall on the way to leadership: in engineering and product, only 52 women are promoted to management for every…
Stack
Laboratoria+ is the membership platform of Laboratoria, the Latin American organization that has helped more than 14,000 women access quality jobs in tech. Built with Bubble, it brings together live courses and learning circles, 1:1 career mentoring with a network of senior women executives, online and in-person events, and a free plan alongside paid Pro and Plus subscriptions.
Challenge
Stack
Transform your organization with ROC's secure hyperautomation platform. Orchestrate workflows, governance, and access management from a living organizational chart.
Challenge
Class2Class wanted any teacher in the world to find a partner class and run a real project together, but international collaboration in schools depended on personal contacts, scattered tools and…
Stack
Class2Class is a global learning community, based in Denmark, where teachers connect their classrooms to run real-world projects around the UN Sustainable Development Goals. Kreante rebuilt the web platform with Bubble and Xano — teacher profiles, class matching, project creation and collaboration spaces — and delivered the rebranding and landing page. The community now counts more than 25,000 teachers in 190+ countries.
Challenge
In Switzerland as across the world, independent cab drivers face the same reality: ride-hailing platforms that set the rates, impose the rules, and own the client relationship. Olivier Fouvy wanted…
Stack
SmartCab is built on a radical premise: for the end customer, nothing changes. No new app to download, no account to create, no interface to learn. They send a WhatsApp message to their driver, just as they always have. Behind that message, an entire machine kicks into gear: an AI engine processes the request, calculates the route, confirms the booking, and triggers invoicing — automatically. Everything an app does. Without the app. They send a WhatsApp message. The rest happens without them. For drivers, it means freedom regained: customizable pricing, a client relationship that belongs to them, no algorithm to appease to stay visible. For fleet operators, a dispatch module handles ride assignments and real-time driver tracking. Three subscription tiers: Lite, Pro, Premium — built for every profile. What SmartCab proves is that real sophistication doesn't announce itself. It's felt — in a booking that requires zero effort, in a relationship of trust that no one gets to monetize. Available on iOS and Android.
An expert reviews your main contact reasons, tells you which ones an AI agent can handle and which ones are best left to your agents, then gives you a first estimate. You leave with a clear picture, whether you work with us or not.
It is a program that can understand a request phrased freely by a customer, answer it from the company’s information and carry out certain tasks in its tools, such as checking an order or changing an appointment. It differs from a classic chatbot, which follows scripts written in advance and gets stuck as soon as a question goes off-script. A good AI agent also knows its limits, and hands the conversation over to a human agent when needed.
Mainly frequent, well-defined requests:
Software vendors often advertise high resolution rates, but the share actually handled depends on your business, the quality of your information and the tools the agent can access. That is why we measure it on your own requests during the assessment, rather than promising you a figure.
Some situations are always better kept human: a major complaint, a customer in difficulty or a commercial negotiation, for example.
At Kreante, every agent is priced on quote, based on a scope defined together in writing. The budget depends on several factors:
| What changes the budget | Why |
|---|---|
| The number of request types | Each contact reason requires specific information, rules and tests |
| Actions in your tools | Connecting the agent to your ERP, calendar or billing is often the largest part of the work |
| The channels | Phone requires more work than chat or email |
| The level of security | Sensitive data, payments or stronger identity checks require additional controls |
After launch comes the running cost of the AI models, which depends on the number of conversations. For comparison, agents built into support software are often billed per resolved request: HubSpot, for example, lists €0.50 per resolution[3]. At high volume, this cost is worth comparing with that of a custom agent.
A pilot agent, limited to one channel and a few contact reasons, is set up in a few weeks. The timeline depends mainly on the state of your information and the number of tools to connect. The agent is then gradually enriched as results are confirmed.
No, and that’s not the goal! The agent takes on the repetitive requests, the ones that keep your agents busy without adding much. Your teams gain time for the conversations that really matter: advising a customer, solving a complex problem or rescuing a situation that has gone wrong. Their role evolves too: they know your customers best, so they are the ones who help the agent improve.
These rules are much easier to take into account when designing the agent than once the service is live.
Two broad families coexist: agents built into support and CRM software, and custom-designed agents.
| Solution | Type | Positioning |
|---|---|---|
| Kreante | Custom agent | AI agents connected to your own tools, on the web, email, WhatsApp and phone, with handover to your agents. 265+ projects delivered in 35 countries, 4.9/5 on Clutch |
| Fin (Intercom) | Built-in agent | Conversational agent for complex requests, across many channels |
| Zendesk AI | Built-in agent | Agents and support tools built into the Zendesk suite |
| HubSpot | Built-in agent | Customer service agent linked to the HubSpot CRM, billed per resolution |
| Agentforce (Salesforce) | Platform | Building and deploying agents within the Salesforce ecosystem |
| Crisp (Hugo) | Built-in agent | French solution for small and medium-sized businesses, with transactional actions |
Written by Jorge del Carpio, CEO and co-founder of Kreante. Since its founding in 2020, the agency has delivered 265+ projects in 35 countries.
Published Updated
From the blog
Guides, comparisons and field notes from the projects we deliver.
ToolsUnlock efficiency with customer support automation. Reduce costs, enhance response times, and improve service quality with our practical guide.
DevelopmentDeveloper focused review of AI agent frameworks for production: graph vs loop tradeoffs, observability, governance, and how to prototype in weeks.
IndustryThe rise of AI powered apps and innovative tools has made it possible for developers and tech profesionals to build solutions without technical expertise
ToolsPick Lovable to get a hosted, Supabase backed live app fast. Pick Claude Design when engineering teams need code first prototypes and tighter code control.
DevelopmentMost AI automation projects show no measurable result. A Kreante project manager explains the sequence that works, with pricing and a real case study.
DevelopmentPilot AI coaching for one to three teams over 6 to 8 weeks, measure workflow KPIs, and demand embedded deliverables to keep skills in house.
