What does Tekst add to Salesforce?

Tekst complements Agentforce by extending automation to areas Salesforce can’t natively reach. It ensures that data entering Salesforce is already structured, clean, and actionable — enhancing Einstein and Agentforce performance rather than competing with it directly.

How does Agentic Process Automation differ from traditional automation tools like RPA?

While RPA follows predefined rules, Tekst’s Agentic Process Automation interprets intent, reasons contextually, and adapts in real time. It can manage unstructured data such as emails or customer requests, making automation far more flexible and intelligent than RPA.

What makes Tekst more flexible than Agentforce for enterprise automation?

Tekst goes beyond Agentforce by automating not only CRM tasks but also the upstream communication that feeds into Salesforce. It captures, cleans, and classifies unstructured data from inboxes, giving enterprises a complete and accurate operational view.

The

alternative

RPA 2.0: Understand work before automating it.

Tekst reads the emails, tickets, orders, and exceptions that make bots brittle and implementations drag for months, then maps the real process and automates it end to end. Live in less than a week, no developers required.

The world’s leading enterprises can now automate with confidence.

Why Tekst?

RPA automates what's structured. Your real work lives in emails, PDFs, and chats: unstructured. UiPath assumes you already know your process and can script it. Renaming bots "agents" doesn't change the architecture underneath.

Tekst starts where the work starts. It understands every message, maps the real process behind it, and executes end-to-end with AI agents, across SAP, Salesforce, ServiceNow, and your inbox.

Tekst AI agents connecting email, PDF, and chat to SAP, Salesforce, ServiceNow, and inbox

Bots Automate Clicks. Here's What Actually Moves the Work.

Scripted automation is only half the job. Here's what closes the gap between a bot and a finished process.

Capability

Where it starts

The AI underneath

Time to value

Maintenance

Cost structure

Team required

At the inbox. Unstructured emails, PDFs, and chats become structured, auditable actions.

A custom model trained on your historical emails, terminology, and languages — default behavior, from day one.

Under 2 weeks. Connect Outlook, ingest history, model trains automatically.

Self-improving. AI reads meaning, not pixels — format variance and new templates handled without re-scripting.

Standalone entry, per module. No platform subscription, no CoE, no user-license minimums, no six-figure services.

None dedicated. No automation CoE, no RPA developers — your ops team owns it.

At structured screens and event logs. Email work needs add-on modules, metered per message.

Pre-built NLP trained on general datasets. Domain accuracy requires AI Center investment and MLOps capability.

Months. Platform deployment, CoE involvement, connector configuration, AI Unit provisioning.

Permanent. Bots break on UI and format changes — and even the Healing Agent that fixes them is metered per fix.

Platform subscription first, then AI Units per message, user licenses per module, plus six-figure Year-1 services. Only the entry tier has a public price.

Automation CoE, RPA developers, and ongoing platform management before automation scales.

TIMELINE FOR COMPARISON: A full platform deployment for email use cases typically involves platform setup, CoE involvement, AI Unit provisioning, and connector configuration — months before the shared inbox problem is touched. Tekst connects to Outlook and delivers first automation results in under 2 weeks.

Already running

keep it.

Your bots work great: once data is in SAP. Tekst is the layer in front.

If 40% of your invoices arrive by email before your bots can touch them, the gap isn't your RPA — it's everything upstream of it. Tekst reads the email, extracts and validates the data, and hands clean, structured input to the systems and automations you already run. Email in → Tekst understands, extracts, validates → your ERP and existing automation execute. The last manual gap in the process closes, without replatforming anything.

See how it fits your stack

Order Entry (email-to-ERP)

extracts order data regardless of format variance, pushes directly to SAP. 75%+ reduction in manual entry.

Shared Inbox Management

90%+ auto-classification; emails routed in seconds, not hours.

Accounts Payable

captures the invoice, validates against PO, routes exceptions. AP cycles from 12 days to under 48 hours.

Customer Service Triage

classifies by type, urgency, segment; drafts responses. 200%+ improvement in first response time.

Multilingual Operations

custom AI trained on your actual multilingual content.

How it works

Conversation Mining

Every email, PDF, and message understood, not just captured. Tekst extracts intent, urgency, topic, and references from free-form language with enterprise-grade accuracy. The unstructured backlog becomes structured, actionable data.

Process Intelligence

Tekst reconstructs what actually happens across systems, teams, and channels, showing where time, loops, and rework accumulate. You automate the steps that matter, with proof, not guesses.

Agentic Execution

AI agents that finish the job across SAP, Salesforce, ServiceNow, and email. They create the case, update the order, route the exception, and reply , with a full audit trail on every action.

Understand First, Then Automate

UiPath automates what you script — process mapping is a separate product with its own user-license minimums and AI Unit activation floor.

Tekst maps the real process first, then automates it. Insight and execution never leave the platform.

Custom AI, Not Generic NLP

UiPath Communications Mining runs pre-built NLP on general datasets — domain accuracy requires AI Center investment and MLOps capability.

Tekst trains on your own email history by default. Your terminology, your workflows, your languages.

Live in Under 2 Weeks

A full UiPath deployment typically takes months: platform setup, CoE, connector config, AI Unit provisioning.

Tekst goes live on your existing stack in under 2 weeks — no CoE, no change management.

A Lower Floor, No Platform Tax

UiPath requires the platform subscription before any module — then meters AI Units per message, with separate user licenses and Year-1 services on top.

Tekst starts standalone, priced per module. Typical Year-1 cost is a fraction of a platform deployment.

See Tekst on Your Own Processes

Book a session with an automation expert. No generic pitch : we'll walk through your workflow and show you exactly what Tekst would automate.

A walkthrough built around your use case : orders, claims, AP, or shared inboxes

Conversation mining live on real examples of unstructured work

The automation opportunities in your process, ranked by impact

A concrete rollout plan: what goes live first, and when

We already run UiPath Communications Mining. Why add Tekst?

Start with one number: your current auto-classification rate. Comms Mining runs pre-built NLP trained on general datasets — powerful, but not trained on your terminology, which is why many teams find their rate sitting below 80%. Tekst trains a custom model on your own email history from day one and reaches 90%+ auto-classification. If your shared inbox is still being triaged by hand, the module you own isn't solving the problem you have.

Won't UiPath eventually build this natively?

UiPath has a strong roadmap — but a roadmap doesn't process the emails arriving this quarter. Custom model training on your own data with a sub-2-week deployment is Tekst's core focus today, not a future release. The real question is what the manual process costs you each month while you wait.

Is Tekst enterprise-grade, or too small for us?

A fair diligence question. Tekst is SOC 2 certified and GDPR compliant, with a full audit trail on every automated action, and runs at global enterprise scale at Becton Dickinson, FrieslandCampina, Nokia, and Mitsubishi. Customer references are available, and a proof-of-value engagement lets you validate results on your own data before any full commitment.

Is there a minimum email volume?

Tekst's modules are matched to your volume: high-volume operations run full Conversation Mining, while per-action pricing on the Process Automation module fits mid-volume teams. A quick volume assessment — part of the demo — tells you which fits, and most growing teams cross thresholds faster than they expect.

We tried AI before — it didn't understand our business.

That's exactly why Tekst exists. Generic AI fails in specialist environments because it was never trained on your language. Tekst's model is trained on your own historical emails from day one — your terminology, your exceptions, your workflows, in every language your teams operate in. It's the difference between hiring someone fluent in your business and someone who's read a textbook about it.

We don't have budget for another platform.

Tekst isn't another platform — there's no platform subscription, no CoE, no six-figure implementation. And run the math on what you're already paying: a team spending 30 hours a week manually triaging email before data reaches your systems costs roughly €50–80K a year in labor alone. On email-heavy use cases, Tekst typically pays for itself within a quarter.