Agent Builder

Teach an agent the way you'd teach a new hire, then deploy it everywhere your team works.

U.S. patent pending

Build your employee in seconds

Feed the engine your documents, databases, live voice, videos, or just a few examples. The Adaptive Reasoning Engine models the brain in seconds, then exposes the same employee across Slack, WhatsApp, email, your website, and an API.

TEACH

DocumentsDatabasesVoiceVideoExamples

ADAPTIVE REASONING ENGINE

Patent pending

YOUR EMPLOYEE

Live in seconds

DEPLOY

SlackWhatsAppEmailAPIWeb

Documents

Drop in PDFs, contracts, decks, or recordings. The agent ingests the content, the structure, and the figures.

Databases

Point the agent at your ERP, CRM, HRIS, or warehouse. It reasons against live records, not snapshots.

Live voice + TTS

Walk through the workflow live, the way you would with a new hire. Docana turns it into a reasoning model. The agent talks back via TTS for hands-free workflows.

Video

Record your expert reviewing a real document or contract. Docana captures the decision logic frame by frame.

Examples

Drop in a few good and bad cases. The Adaptive Reasoning Engine learns the pattern and the boundary.

No prompt engineering. No ML team. No code. Your subject matter expert teaches the agent the way they would teach a new hire, and the deterministic core handles the rest.

Compose your team

Docana started as a tiny team with too many jobs for too few people, so we built agents to do the work and called them super employees. Now you can hire the same six inside your enterprise: finance, sales, support, legal, ops, and a Business Analyst on top. Each one is bounded to the data you decide and validated by deterministic LLM evals before it acts.

Every conversation becomes a data point

Define the KPIs your business actually cares about. Every conversation runs through deterministic LLM evaluations that extract sentiment, intent, resolution status, escalation needs, and any custom field you define. The result is a live dashboard your team actually reads, and an agent that learns from every interaction.

platform.docana.com / agents / customer-support / stats
7 DAYS30 DAYS90 DAYSLIVE

Total executions

12,847

+18%

Success rate

99.1%

+0.4%

Avg duration

17.8s

−2.1s

Error rate

0.9%

−0.3%

Customer sentiment

Extracted on 12,847 of 12,847 conversations

Neutral53%
Positive36%
Negative11%

User intent

Top reasons users reached out

Pricing inquiry
38%
Product information
24%
Schedule a viewing
16%
Status update
12%
Cancellation
6%
Other
4%

Insight extracted · today

User asked about beach-property investments in coastal states served by Moura Dubeux, specifically about projects in Praia dos Carneiros. The assistant listed line options.

Sentiment:NeutralIntent:Pricing inquiry

Define your KPIs

Sentiment, intent, resolution, escalation, urgency, custom fields. Whatever your business measures, the agent learns to extract it.

Auto-extract via LLM evals

Every conversation runs through deterministic LLM evaluations that pull structured data points back, scored and ready to query.

Dashboards your team reads

Distributions, trends, drill-downs, and per-conversation traces. Filter by any KPI to find exactly what your customers asked yesterday.

Agents that learn over time

Insights from past conversations carry forward. The next time a customer reaches out, the agent already knows what happened last time.

Insights flow back into the agent's memory. The next conversation knows what happened in the last one, across users, channels, and time.

Your AI workforce. Live this week.

In a 30-minute demo we'll wire Docana™ into a sample of your data and show you what the Enterprise Reasoning Layer surfaces in the first hour: leakages, anomalies, missing controls, and the work your first agent can absorb on day one.

Scale output, not headcount.

Request a Demo