We launched our new Conversational AI platform for enterprises

We're launching our new B2B Conversational AI platform: a structural leap that bundles years of lessons from high-volume customers into one environment. This is not a feature pack on top of the previous generation: it is a full rebuild of our stack, designed for speed, scale, mobile, internationalization and the pace of change generative AI demands in production.

We start from a simple, demanding premise: conversation stops being one channel among many and becomes the primary interface between customers, teams and internal systems. Instead of phone queues, rigid forms or keypad-driven bots (which break when intent drifts from the script). The operation works in natural language, with history, CRM context and brand-aligned business rules.

Why we rewrote the platform, not just updated it

In October 2025, we began rewriting the product. After two years in conversational AI, it became clear that the platform that brought us this far would not reach the next level: volume, deep integrations, enterprise governance and iteration speed the market now expects.

The rise of vibe coding and new development paradigms reinforced our decision: we needed a new foundation in architecture, performance and experience, not patches on top of 2023 choices. Selected customers already run the new platform; in the coming days, we expand rollout to the installed base, alongside the new site at tolky.to.

If you're evaluating automation platforms, the message is direct: we're entering a new growth phase focused on organizations where interaction volume, legacy integration and governance cannot live in fragmented tools.

The problem we're solving with this generation

We see most enterprises with huge message volumes operating on a mosaic of tools: a CRM, a helpdesk, a WhatsApp sender, BI spreadsheets, generic automations and, on top, a chatbot that does not truly talk to any of it.

The symptoms are predictable:

• Customers repeat context at every handoff or channel switch
• Marketing launches campaigns, but service does not see lead origin
• Finance resolves invoices in one system; support does not know the bill was already sent
• Management exports CSVs for reports; conversations do not become data in real time
• AI looks great in demos but does not write to the ERP or honor exception policy

We built this generation to attack that pattern with an integrated conversational ecosystem: service, management and intelligence on the same omnichannel layer, without hiding complexity behind outdated menus or promising a "magic bot" in the corner of the site.

AI-first architecture: AI at the center, not on the surface

For us, AI First means artificial intelligence is not limited to a superficial text layer. It runs through:

• Dynamic knowledge base: approved, versioned, curated content, not unconstrained hallucination
• Conversational CRM: every message updates pipeline, tags and next steps
• Human console: when someone takes over, context is already assembled
• Active campaigns: outbound and follow-up share the same history as inbound
• Semantic voice: web, WhatsApp and phone (smart IVR) in one operation
• Integrations: ERPs, finance and corporate data when resolution requires reading or writing real records in the customer's infrastructure

The outcome we're pursuing is not only "automation to shrink headcount." We want higher volume with quality, lower cost per contact, faster first response and a guarantee that when a human joins after the AI, they already know why the customer wrote in, what was tried and what sensible next step follows.

Context-aware handoff (history, intent, CRM data and explicit escalation reason) is central to our value proposition, not a UX detail.

Our operations and BI dashboard

The conversational ecosystem: five fronts, one operation

We organized the product into five connected fronts, from first contact to operational intelligence. Everything shares the same thread of context; not modules you "integrate later."

Instead of stacking Service + CRM + Contacts + Content + Departments + Flows + Campaigns + Automations + Alerts + Follow Up + AI Forms + BI across vendors, we concentrate that ecosystem in one operation connected to the customer's data.

The five pillars of our launch

1. AI-first architecture

Conversational resolution at the center, with generative models wired to approved knowledge, business rules and CRM context, not a standalone LLM answering without memory or policy.

2. True omnichannel

WhatsApp, web chat, semantic voice (web, WhatsApp and phone) and SMS in one operation with unified history. Customers do not "start over" when switching channels; teams do not lose the thread on escalation.

3. Measurable operations

Native BI, Follow Up, AI Forms and conversational CRM turn customer service into actionable data for management, without parallel spreadsheet workflows or constant manual exports.

4. Context-aware handoff

When AI escalates to a human, the agent sees full history, intent and CRM in plain sight. Customers do not repeat name, order and ticket number for the third time.

5. Enterprise-ready

Documented APIs and a Reasoning orchestrator for critical flows: integrate ERPs, finance and corporate data with governance, curation and clear boundaries where the company always prefers a human in control.

Our conversation workspace

AI CRM for the conversational era

Our positioning is explicit: we're not "another bot." We're relationship infrastructure for an era when businesses and customers already talk via message, audio and voice, not only forms and email.

We're the Conversational AI platform that turns customer service, sales and relationships into an intelligent, omnichannel and humanized operation.

AI CRM for the conversational era. Relationships became conversational; we bring service, management and intelligence into one living ecosystem.

Three axes sustain that vision at once:

The market we see: beyond "magic bot" hype

Brazil's generative AI market has matured. Operators want SLAs, security, traceability and reports. Marketing and sales need conversion and pace in first replies after campaigns. Finance needs negotiation and payment copies on the right channel, without friction.

The shift underway is from form-, queue- and menu-driven operations to intelligent conversation-driven operations. Enterprises with huge volumes in care, sales, collections, support and lifecycle must serve more people with higher quality in less time, without losing personalization or control.

We believe mature Conversational AI is how you scale without multiplying operating cost or degrading CX. That's why we position this platform as infrastructure for those outcomes, not a static widget.

The next generation of enterprises won't only be digital. They'll be conversational, intelligent and integrated, able to serve at scale without treating people like numbers.

Our manifesto

Enterprise trajectory and what we learned in the field

Our trajectory includes institutional and industrial clients with major public impact, including a public case with Brazil's National Council of Justice (CNJ) and large brands that depend on true omnichannel reach, such as the Volvo case in automotive.

The governance, traceability and legacy integration bar those profiles require shaped this product generation: documented APIs, Reasoning for critical flows, curated knowledge and controls where regulated sectors or internal policy require a human on the final decision.

With this new structure, we serve organizations where volume, legacy and compliance do not fit in shallow automation layers or disconnected SaaS stacks.

Our automation and orchestration

Applications by area

Our platform serves enterprises with high volumes in customer service, sales, marketing, collections, technical support, Customer Success and HR. Our modular design lets you connect what hurts most today first and expand without swapping stacks.

Deep integration: what separates curiosity from product

Patrick Bonnereau, our co-founder, puts it well:

When AI talks to ERP, finance, CRM and operations in real time, the company stops patching tools together and starts operating with end-to-end context.

Our bet is AI First with governance: scale with maturity, not empty promises. That includes architecture for continuous evolution, response quality metrics, human handoff with context and a technical base that sustains growth without sacrificing experience.

Operational intelligence and reporting

What our founders say

Marlos Carmo, co-founder:

Last October we started rewriting Tolky. After two years in conversational AI, it became clear that the platform that brought us here would not take us to the next level, and that the rise of vibe coding calls for a new foundation in speed, scale, mobile and internationalization.

That is why we rebuilt everything. We are launching the new site at tolky.to: some customers are already testing the new platform and, in the coming days, it will start reaching everyone. A new phase for Tolky.

Patrick Bonnereau, co-founder:

Deep integration with the customer's systems is what separates curiosity from product. When AI talks to ERP, finance, CRM and operations in real time, the company stops patching tools together and starts operating with end-to-end context.

Our bet is AI First with governance: scale with maturity, not empty promises. That means architecture ready for continuous evolution, clear metrics on response quality, human handoff with context and a technical base that sustains growth without sacrificing experience.

FAQ about the launch

Does the new platform replace the current version immediately?

No. Our rollout is gradual: selected customers already run on the new stack; we expand the base in the coming days. Our customer success team accompanies migration of channels, knowledge and integrations per account plan.

Do I need to migrate all channels at once?

No. Our modular design lets you start with the highest-pain channel or process (e.g. WhatsApp + lead qualification) and expand to voice, SMS, full CRM or Reasoning with ERP later.

How are we different from a chatbot + Zapier?

An isolated chatbot answers text; it does not operate as a relationship layer with live CRM, SLA, native BI, governance and multi-agent orchestration. Zapier connects apps but does not unify conversational operations or native context-aware handoff; the company remains the integrator. We deliver the full ecosystem.

Does the platform meet enterprise requirements (LGPD, audit)?

Yes. Our governance front includes immutable history, audit logs, SSO, encryption and operation with data on servers in Brazil, aligned with requirements already demanded in public sector and industry.

Where is the official press release?

Journalists and editorial teams can access the release, media kit and fact sheet on our press page, with materials in Portuguese, English and Spanish.

Next steps

Our new platform is already rolling out to selected customers and reaches the full base in the coming days.

• Explore the ecosystem on our features page
• Schedule a 30-minute demo with our solutions team
• Create your avatar and try it at tolky.to

For editorial coverage: negocios@tolky.to · materials at /press