AI for organizations
Agents for specific tasks. On one engine for your company.
We have agent modules that we adapt to your process, and when none fits, we build a custom agent. Each one runs on AI Engine: your company’s knowledge, rules and system connections.
Agent modules
Modules we adapt. Or an agent built from scratch.
Every module grew out of an implementation for a client. When another company needs a similar process, it starts from a ready pattern: Skills, integrations and acceptance criteria, not from scratch.
- 01
Quoting agent
Reads enquiries, selects products and prepares quotes. The team checks the result before sending it to the customer.
Explore the solution - 02
Knowledge agent
Answers questions using company knowledge. Points to current sources in the tools the team already uses.
Explore the solution - 03
Document agent
Reads documents and checks completeness. Passes data onwards and routes exceptions to a person.
Explore the solution - 04
Product agent
Selects and configures products using company rules. Connects parameters, availability and documentation.
Explore the solution - 05
Tender agent
Brings together requirements, deadlines and attachments. Helps prepare a response for the team to review.
Explore the solution Custom agent
We build an agent for the process you choose, starting with a feasibility study. That is how our Quoting agent started too.
Explore the solution
AI Engine
It’s not about which agent. It’s about what it runs on.
Modules and custom agents run on the same AI Engine in your company. What we prepare for one agent stays in AI Engine and shortens the path for the next one.
- The same knowledge and rules for every agent.
- We build system connections once, and the next agent uses them.
- A person approves the result wherever the decision belongs to the team.
Case studies
Every implementation fitted to the company’s process.
We describe clients anonymously. The status shows the stage of each implementation.
In production
The quote reaches the client before the competition’s.
7 days → 1 day
response time for enquiries handled by the agent
See the case study
In progress
Financial statements and reports without manual retyping
80-90%*
about 3 min instead of 15-30 min of retyping
See the case study
MVP
Product selection in a few minutes, rather than an hour.
up to 1 h → <10 min
pilot target: product selection time
See the case study
In production
Company knowledge available in Teams
14 weeks
from kickoff to a Knowledge agent in Teams answering from FAQs, documents and product data
See the case study
Work in progress. These are results verified at the test stage or the targets we are aiming for. We will confirm them on completion.
Measuring results
Value you can check.
Before implementation, we agree with you on a baseline, a target and a success threshold. After implementation, we measure from the same point, in the areas where the solution creates value.
Time saved
The same team handles more work and spends less time on routine tasks.
Sales and revenue
Faster quotes and smoother service help you respond to customer needs.
New possibilities
Your company can review more information, respond sooner and start work that previously lacked resources.
How we work together
Working with your team. From ambition to everyday work.
Every project is led by an AI consultant and an AI engineer, backed by the WeAreFuture engine. For adoption programs, an adoption specialist joins them. We support you from the first process to further use cases.
From us, inside your company
- AI consultantdirection, priorities and business value
- AI engineerdata, agents and integrations
- Adoption specialistfor adoption programs: people, skills and new working practices
WeAreFuture engine
agent modules, Skills and methodology from previous projects
Your company
- Sales
- Customer service
- Purchasing
- Production
- Logistics
- Finance
AI Engine data, procedures and system connections from every department
A team that gets to know your company
The AI consultant agrees priorities with leaders, while the AI engineer handles the solution and integrations. For adoption programs, the adoption specialist helps people adopt new working practices.
Agent modules and a shared methodology
We bring agent modules and a way of working that connects processes, data and value measurement. Integration is adapted to your environment.
Your engine grows with every department
Data, procedures and system connections stay with you. The next department builds on what the previous one created, so it doesn’t start from scratch.
Client testimonial
“If you want to succeed in today’s digital reality, this is exactly how to work together.”
“(…) we had made a basic mistake: we got carried away by the technology without defining a comprehensive company strategy. (…) We paused the projects under way and focused on finding an experienced partner who would co-create our AI strategy with us, train (…) technical teams and users, and help turn our ideas into functional AI applications (…). From an idea to the first working version takes a dozen or so days at most.”
Read the full testimonialCollapse
At Smay, we began exploring how artificial intelligence (AI) could support our business processes right after AI solutions became widely available. The decision to enter the field of AI was beyond question. We concluded that there was no turning back from this path, and that it is far better to lead the pack than to be in the middle or, heaven forbid, at the back.
We went straight into delivery. Several projects (e.g. an internal HR bot) reached beta testing, but at some point we concluded that we had made a basic mistake: we got carried away by the technology without defining a comprehensive company strategy. AI is a tool, so we should use it in our work, and AI should bring us measurable benefits. We knew that we were a leader in ventilation, but not yet in AI.
We paused the projects under way and focused on finding an experienced partner who would co-create our AI strategy with us, train technical teams and users at different levels, and help turn our ideas into functional AI applications that bring tangible benefits, especially financial ones. Finding a partner with real knowledge and experience was not easy at all. The market is full of companies advertising themselves as AI specialists, but their experience and portfolio do not match.
We started working with WeAreFuture by improving our quoting process. Because the idea is original, I can only mention that the AI we developed together, code-named Alina, can already prepare a sales quote for a customer on its own, responding to a request sent in any form, even an informal one. An internal assistant also works in the company, answering employees’ questions about internal procedures and providing information about our products.
The solutions we have deployed already run in production and take excess work off the team. The synergy we achieved by working side by side with the WeAreFuture team greatly increases the effectiveness of the solutions. From an idea to the first working version takes a dozen or so days at most, which lets us assess results quickly and make corrections.
We greatly value the WeAreFuture team’s ability to work within everyday system constraints, their flexibility in quickly finding effective solutions and their focus on measurable, functional goals. Our cooperation can be summed up in one sentence: if you want to succeed in today’s digital reality, this is exactly how to work together.
Translated from Polish.
Grzegorz KawalerCIO, Smay Ventilation SystemsHow to start
We choose the first step based on your goals and readiness.
AI consulting starts with a diagnosis: a readiness check, Discovery or a board session. We then deliver AI implementations process by process, on a single AI Engine.
- You know which process
Module or feasibility study
If a module fits, we agree on data, integrations and acceptance criteria. If not, we start with a two-week study on your data.
- You don’t know which process to start with
Discovery
We show where AI will pay back the most. You get use cases ranked by value and a recommendation for the first implementation.
- The board wants the whole change led
AI Start in 90 days
Our AI consultant inside your company for a quarter: roadmap, rules and adoption framework. You decide on the next step.
Want to check your company’s readiness first? AI Check, 20 questions, about 7 minutes
Questions
Frequently asked questions.
What is AI Engine?
The AI Engine is a shared company context used by people and agents. It consists of data about customers and products, procedures written down step by step and decision rules, connected to your systems. We build it in stages, process by process. Corrections and decisions from everyday work flow back into it once the process owner approves them, so every next agent starts faster. More on the AI Engine page.
Do we have to choose one of your modules?
No. First, we check whether one of the modules is enough: quoting, company knowledge, documents, product selection or tenders. When none covers your process, we build a custom agent. In that case, we start with a two-week feasibility study on your data. Modules and custom agents run on the same AI Engine.
Do the agents work with our systems, such as ERP and CRM?
Yes. We connect ERP, CRM, Microsoft 365 and Helpdesk to AI Engine, and MCP gives agents controlled access to agreed tools. The modules also use SharePoint, Teams and email. We confirm the integration scope after reviewing data, permissions and interfaces. A connection built for one agent stays in AI Engine, and the next agent uses it. More about system integrations.
Who approves the agent’s output?
Your team. The agent prepares the result, and a person approves it and resolves exceptions. Before the start, you name the person responsible for approval. In quoting, a consultant approves the quote before further processing in ERP; in tenders, the team assesses the terms and decides whether to submit a bid.
Does our data have to leave the company?
Azure is the starting point. The most sensitive data can be processed by local models on company servers. We select other clouds and fully on-premise environments together with IT. More about the AI environment.
Where do we start?
With a conversation about one process where repetitive work holds your team back. If a module fits it, we agree the data, integrations and acceptance criteria. If none fits, we start with a feasibility study. If the board needs direction first, there is AI Start in 90 days. If you don’t know where to start, AI Check gives you a picture of your situation and three actions to plan, in about 7 minutes.
Let’s talk about agents in the organization.
We start with a specific process and the expected outcome. Together, we review the data, integrations and scope of the first AI Engine module.
Book a callOr write to: hello@wearefuture.ai


