AGENT PLATFORM

Agents in production without standing up a data platform

Aracely AI is a platform where agents are built, tested and published from an interface, over your own documents and wired to the systems you already use. It is the short path when the case does not justify a streaming platform, and we run and integrate it.

No commitment · 30 minutes · With a senior architect

  • Unlimited agents on every plan
  • Monthly plans from USD 99
  • On their cloud or yours
WHEN IT MAKES SENSE

Not every company needs an event platform to use agents

A bank with twenty systems and a regulator watching needs an event backbone. A two-hundred-person company with a CRM, an ERP and a lot of documentation does not. It needs someone to be able to ask that documentation a question, and the agent to act on the systems that already exist.

The knowledge is in documents, not in events

Manuals, policies, contracts and procedures. The problem is not data latency, it is that nobody finds the answer when they need it.

There is no platform team

Nobody is going to run a cluster or maintain pipelines. Whatever is bought has to work without hiring a new department.

The budget is monthly, not a project

The decision gets made on a predictable, reversible cost, not on an investment that has to be defended for three years.

WHAT THE PLATFORM BRINGS

What an agent needs, without building it

The capabilities come solved. Our job is picking the case, wiring your systems and leaving it running.

Knowledge base with RAG

The agent answers from your documents

Upload PDF, DOCX, TXT and Markdown, and the platform indexes and chunks them for semantic search. The agent retrieves the relevant passage and answers from it instead of inventing one. Knowledge bases are shared across agents or isolated per case.

For whoever has the knowledge written down and scattered.

Connectivity through MCP

The agent acts, it does not only talk

Connections to CRM, databases, email, storage and your own APIs through MCP, REST and webhooks, with six authentication methods. It is the same protocol we use on the streaming projects, so what gets wired here is not lost later.

For whoever needs the agent to do something, not to reply.

Several models, one place

The model is picked per use case

Models from OpenAI, Anthropic, Google and Groq, swappable without rewriting the agent. The higher plans include real-time cost tracking, and the self-hosted edition takes your own models through vLLM and Ollama.

For whoever does not want to be tied to one model vendor.

Deployment and security

On their cloud or yours

As a managed service, or self-hosted on AWS, Azure, Google Cloud and Oracle Cloud. Role-based access control at company and agent level, CSRF protection, per-IP rate limiting and encryption in transit and at rest. GDPR compliant and SOC 2 ready.

For whoever has data that cannot leave their own infrastructure.

WHERE WE HAVE SEEN IT WORK

Cases that close in weeks, not quarters

These are the patterns the platform solves directly. The order matters: it pays to start with one.

Customer support

Answers from the real documentation, at any hour

The agent answers from the knowledge base and escalates to a human when it runs out.

Internal helpdesk

Self-service for the team, over the procedures that already exist

Cuts repeat ticket volume without replacing the support tool.

Lead qualification

The agent qualifies and syncs with the CRM

It connects to the CRM through MCP, so it writes where the sales team already works.

Regulatory lookup

Search regulatory documents without reading them end to end

Semantic search over the regulatory corpus, with the source cited in the answer.

WHAT WE DO

From a licence to an agent somebody uses

Buying the platform is the easy part. What decides the outcome is picking the right case and wiring it to the right systems.

  1. 1 WEEK

    01. Pick the case

    We look at where time is lost today and what documentation exists. We come out with a defined case and a measurable success criterion.

  2. 2 TO 4 WEEKS

    02. Set up and connect

    We load and organise the knowledge base, configure the agent and wire it through MCP to your CRM, your databases or your APIs.

  3. ONGOING

    03. Tune on real usage

    We review the conversations, correct what the agent gets wrong and widen the scope once the first case works.

Products

Does your case fit here, or does it need more?

In half an hour we tell you whether this platform solves your case, or whether what you need is an event architecture. Both answers are useful and neither costs anything.

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