Product: AI Agents
AI Agents built into your business processes, able to understand context, access data, use tools and take action.
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What an AI Agent is
What it’s made of
An AI Agent is not a single model. It is a system that combines AI, data, knowledge, tools and rules to achieve a goal within a business process.
It can access documents and databases, query CRM and management systems, use APIs, understand different inputs and take action on connected systems.
Architecture, infrastructure and level of autonomy are defined around the use case, with security, Human in the Loop and monitoring built in where needed.
How it works
We map the goals, users, data, systems, constraints and tasks the Agent will need to support or handle.
Current process
5 steps · all manual
Mapped process
Every step is classified: the Agent only handles what falls within the defined scope.
We define the models, knowledge, integrations, tools, permissions and level of autonomy best suited to the process.
Agent blueprint
Spec v0.3 · draftOrchestrator
AI Agent
We develop the Agent, connect business data and systems and build the interfaces it needs.
Agent integration
Environment: staging01Business systems
02Agent
AI Agent
03UI touchpoints
04Users
We validate the Agent’s outputs, actions, exceptions, security and behaviour before it goes into production.
Eval suite
AI Agent
Validated and ready for release
6/6 dimensions validated
We set up monitoring, logging and KPIs to observe the system and help it evolve over time.
Measurable value
40%
Operational tasks absorbed
6 mo.
To first ROI
30+
Agents in production
Tailor-made
There is no single kind of AI Agent. It can work behind the scenes on a process, support a team in its daily work or interact directly with customers, suppliers and staff.
Interfaces, channels and systems are chosen around the use case, so the Agent fits into the tools the company already uses without creating a new parallel process.
Let’s talk about your agentWho it’s for and use cases
The sales team defines the ICP, territories, company size and exclusion criteria. The AI Agent analyses sources and databases, finds matching companies and contacts, enriches the profiles and returns a pipeline of B2B leads that are already qualified and prioritised. Sales reps no longer start from raw lists, but from opportunities already assessed against the sales strategy.
Every sales proposal goes through an AI Agent used as part of the company process. The Agent pulls data from the CRM, applies approved templates, pricing, claims and rules, generates consistent pitches and proposals and records the information used. The result is a more traceable, standardised sales process that follows company practice, even when different people or teams are involved.
On complex opportunities, the Agent analyses CRM history, contacts, previous offers, call notes, documents and signals that emerged during the negotiation. It highlights risks, missing stakeholders, recurring objections and possible levers, suggesting strategy and next steps to the sales rep. AI does not replace the relationship: it raises the quality of decisions before the key moments.
What you get
AI Agents take on repetitive tasks, checks, research and operational steps, increasing team capacity without a proportional increase in workload.
Rules, guidelines and ways of working are applied consistently, reducing differences between people, sites or teams and making the process more traceable.
Tasks that can be automated are handled by the Agent, while exceptions, judgement, relationships and sensitive decisions stay with people.
Thirty minutes. We start from your use case and work out together where an AI Agent can create value in your organisation.
Book a free callPrefer to write to us first? sales@booons.ai
No. An AI Agent can talk to a person, but it doesn’t stop at answering. It can access data and systems, use tools, apply rules, take action and carry out tasks within a business process.
Yes. We start from the real use case, the existing systems and the level of autonomy required. Architecture, models, knowledge, integrations, interfaces and controls are defined around the process the Agent needs to support.
Yes. Agents can connect to CRM, ERP, databases, management systems, documents, APIs, portals and other business tools. The goal is to fit them into existing processes, without creating a separate ecosystem.
It depends on the use case. Some tasks can be carried out autonomously, while others may require confirmation, approval or human intervention. Limits are defined at the design stage and can evolve over time.
No. We can use models from OpenAI, Anthropic, Google, other providers or open-weight models, choosing each time the combination best suited to performance, cost, privacy, infrastructure and control.
The Agent is monitored through logging, metrics and evals. We analyse usage, errors, performance and behaviour over time to spot issues, improve the system and measure its real impact on the process.