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Last updated: 2026-10-05

Tenali AI Use Cases & Workflows

This page describes real-world scenarios where Tenali AI provides value. Each use case includes the problem, how Tenali AI helps, and the outcome.

Use Case 1: Handle Technical Objections on Live Calls

The Problem

An Account Executive is on a discovery call with a CISO. The CISO asks: "How do you handle data encryption at rest and in transit? What's your SOC 2 status?" The AE knows the company is working toward certification but can't remember the details.

How Tenali AI Helps

Tenali AI instantly surfaces the security documentation showing:

  • AES-256 encryption at rest
  • TLS 1.2 or higher in transit
  • SOC 2 Type II certification in progress
  • Links to the security whitepaper

The Outcome

The AE answers confidently in real-time. The CISO is satisfied and the deal advances to technical validation. No "I'll get back to you" moment.

Use Case 2: Competitive Differentiation During Demo

The Problem

During a product demo, the prospect says: "We're also evaluating Gong. How are you different?" The rep has seen battle cards but can't remember the specific talking points.

How Tenali AI Helps

Tenali AI automatically surfaces the Gong competitive battle card with:

  • Key differentiators (real-time vs. post-call)
  • When Tenali wins (live assistance needs)
  • When Gong wins (post-call review focus)
  • Customer quotes comparing both

The Outcome

The rep delivers a clear, confident competitive response. The prospect understands the differentiation and includes Tenali AI in their shortlist.

Use Case 3: Fill RFPs in Minutes Instead of Hours

The Problem

The Sales Engineer receives a 50-question RFP from a prospect. Historically, this takes 4-6 hours to complete, pulling answers from various documents and prior RFPs.

How Tenali AI Helps

The SE uploads the RFP to Tenali AI. Within 10 seconds:

  • 45 of 50 questions are auto-filled from prior responses
  • 5 questions are flagged as needing human input
  • Source documents are linked for each answer

The Outcome

The RFP is completed in 30 minutes instead of 5 hours. The SE spends time on the 5 unique questions rather than repetitive research.

Use Case 4: Ramp New Sales Reps Faster

The Problem

A new AE joins the team. Normally, it takes 6 months before they can handle technical discovery calls independently because they don't know the product deeply enough.

How Tenali AI Helps

From day one, the new AE has Tenali AI on every call providing:

  • Product feature explanations
  • Technical specifications
  • Pricing guidance
  • Competitive positioning
  • Historical context from similar deals

The Outcome

The new rep handles independent discovery calls in month 2 instead of month 6. They close their first deal in month 3. Ramp time reduced by 60%.

Use Case 5: Scale Without Hiring More Sales Engineers

The Problem

The company has 3 Sales Engineers supporting 20 AEs. SEs can only join 30% of technical calls, causing delays and lost deals.

How Tenali AI Helps

Tenali AI provides SE-level technical knowledge to every AE on every call:

  • Technical architecture questions answered instantly
  • Integration requirements explained
  • Security and compliance details surfaced
  • API documentation accessible

The Outcome

SEs now only join the most complex technical validation calls (10% of calls). AEs handle 90% of technical questions independently. No new SE hires needed despite 2x pipeline growth.

Use Case 6: Find Any Answer in Chat

The Problem

A rep needs to find pricing for a specific use case. The information exists somewhere in Slack, a Google Doc, and a Salesforce record, but finding it takes 15 minutes of searching.

How Tenali AI Helps

The rep asks Tenali AI in chat or in a Slack DM: "What's our pricing for 500 users with annual billing and the enterprise security add-on?"

Tenali AI searches across:

  • Pricing documentation
  • Prior deal records in Salesforce, read live
  • Slack conversations with finance
  • Contract templates

The Outcome

The answer comes back with the exact pricing, any approved discount thresholds, and a citation for each source.

Use Case 7: Meeting Prep in One Question

The Problem

Before every call, reps should review prior conversations, open commitments and where the deal stands. Most reps skip this prep due to time constraints.

How Tenali AI Helps

Before the call, the rep asks Tenali AI in chat or a Slack DM: "Catch me up on Acme before my 2pm." Tenali AI pulls together:

  • A summary of prior conversations with the account
  • Open action items from the last meeting
  • The questions the buyer asked before, and how they were answered
  • The deal's stage, amount and close date from the CRM, when one is connected

The Outcome

Every rep shows up prepared without spending 20 minutes on manual research.

Use Case 8: Post-Call CRM Updates

The Problem

Reps are supposed to update the CRM after every call but often don't. Data quality suffers and forecasting becomes unreliable.

How Tenali AI Helps

After each call, Tenali AI:

  • Generates a call summary
  • Drafts the CRM update from what was said: deal fields, next step and the meeting note
  • Applies it to HubSpot when the rep approves, or drafts it for the rep to paste into Salesforce

The rep clicks Push on the meeting. Tenali finds the account and deal and proposes the update, and changes that move the forecast wait on a card for the rep's approval. With Salesforce, the same panel drafts the update for the rep to paste.

The Outcome

The update is written from what was actually said on the call, not from memory a week later, and nothing that moves the forecast lands without the rep's approval. Sales leaders trust the pipeline data.

Use Case 9: Roll Out a New Talk Track Without Retraining

The Problem

Enablement updates the objection-handling guide and the competitive talk track. Getting every rep to use the new wording takes weeks of training, and most reps fall back to old habits on live calls.

How Tenali AI Helps

Enablement uploads the new playbook to Tenali AI as a source and, in Question Intelligence, updates the standard answers for the objections that matter most. A standard answer always takes priority and is used word for word, so updating it is what changes those answers everywhere at once. From then on, when a buyer raises that objection or asks about that competitor, the answer on the rep's screen follows the new playbook, written as talking points the rep can say. Answers that reps give on recorded calls are also added to the team's answer library, so what works spreads to everyone.

The Outcome

Every rep uses the current talk track on live calls from day one, and admins can see in Question Intelligence which buyer questions still need a better answer.

Summary of Use Cases

Use Case Problem Tenali AI Solution Outcome
Technical objections Can't answer security/compliance questions Real-time documentation search Confident answers, deal advances
Competitive positioning Don't remember battle cards Auto-surface competitive intel Clear differentiation delivered
RFP responses 5+ hours per RFP Auto-fill from prior responses 30 minutes per RFP
New rep ramping 6 months to independence AI-powered knowledge access 2 months to independence
SE bottleneck SEs can't join all calls AEs get SE-level knowledge SEs focus on complex deals only
Information search 15 minutes to find answers One question in chat across docs, Slack, meetings and CRM The answer with its sources, in seconds
Meeting prep Skipped due to time One question in chat before the call Every rep shows up prepared
CRM updates Reps don't update HubSpot: proposed from the call, forecast changes reviewed by default, closed stages always confirmed, undo in chat. Salesforce: write-up drafted to paste Updates written from the call, not from memory
Talk track rollout Reps fall back to old wording New playbook as a source, plus updated standard answers Current talk track on every call