The sales world has hit a turning point. Buyers want sharper answers, shorter cycles, and zero fluff, and sales engineers are the ones carrying the weight. But here’s the truth few talk about: the teams winning today aren’t the ones working harder; they’re the ones using AI in sales to work smarter.

From RFP automation and proposal generation to demo automation, sales intelligence platforms, and deep technical Q&A, the right AI sales tools can transform the SE workflow. They eliminate repetitive tasks, pull knowledge from scattered systems, and give teams the precision buyers now expect.

If you’re a sales engineer, presales lead, or part of a technical sales org running a modern sales tech stack, this isn’t a beginner’s round-up. This is a curated look at the best AI tools for sales engineers, the ones that actually impact deal velocity, sales productivity, and the buyer journey.

Let’s dive into the tools worth your time.

What are AI sales tools for SEs?

AI tools for sales engineers are software systems that automate and accelerate the technical side of the sales process, everything from discovery research and RFP automation to demo prep, proposal generation, competitive analysis, and technical Q&A. Unlike generic AI sales tools or traditional sales tools, these platforms are built to understand product complexity, buyer context, and the fast-changing needs of enterprise deals.

In simple terms:

AI tools for SEs help technical sellers deliver clearer answers, better demos, and faster proposals, without drowning in manual work.

They plug into the systems SEs rely on every day (Slack, CRM, Drive, Confluence, product docs, call recordings) and act as a real-time co-engineer that can:

• Pull accurate answers from scattered knowledge
• Auto-complete long questionnaires and proposals
• Surface sales insights and deal risks
• Prepare technical narratives and demo storylines
• Automate repetitive workflows inside the sales tech stack

These tools don’t replace sales engineers. They amplify them, giving SEs more time for solutioning, influencing stakeholders, and driving the buyer journey forward.

If your team cares about sales productivity, sales efficiency, or scaling presales expertise across more deals, AI tools for SEs are no longer optional. They’ve become the new foundation of modern AI sales enablement.

Why sales engineering tools are essential in 2026

In 2025, the role of a sales engineer is more complex and more valuable than ever. Buyers want clarity, speed, and personalization. Sales teams want scale, automation, and productivity. Sales engineering tools are no longer “nice to have”; they’re critical for shortening the sales cycle, improving customer satisfaction, and unlocking new efficiencies in technical selling.

Top sales engineering tools in 2026

Category: AI RFP sales tools

1. SiftHub

If you’ve ever looked at a 500-row Excel RFP and thought, “Why does every question sound like a trick?”, SiftHub is the tool you wish someone had given you on day one.

SiftHub isn’t your typical sales tool that promises automation and then hands you another template to maintain. 

SiftHub is an AI sales engineer sitting next to you, one who remembers every Slack thread, every Confluence page, every old deal note, and every piece of technical documentation your team has buried across the sales tech stack.

It pulls real answers from real systems (Slack, CRM, Drive, Notion, Confluence), which is a huge deal because most AI tools for sales rely on outdated content libraries. With SiftHub, you get verified responses that reflect how your product works today, not six releases ago.

Highly recommended for SEs because it genuinely cuts down the mental load, not just the typing.

Features:

• It autofills Word, Excel, PDF, and even those awful vendor portals
• The browser extension is the real hero for RFP automation
• No more bothering SMEs for answers they’ve already written 12 times
• Multi-language proposal generation when you're selling globally
• Works beautifully across sales engineering workflows, not just basic proposal automation
• Predictive accuracy because the answers come from your systems of record

Pro:

• Cuts RFP turnaround time from “end of quarter panic” to “hey, we’re done already.”
• Plays nicely with other AI sales tools and CRMs
• Improves sales productivity because you stop doing manual scavenger hunts
• Feels like actual AI sales enablement, not just another AI writing tool

Cons:

• It’s built for serious teams (mid-market + enterprise)
• Works best when you integrate your stack properly

If you want the best AI tools for sales engineers, this is easily top of the list.

Try SiftHub today. 

2. Responsive

Responsive is the veteran in the RFP automation space. It’s a solid platform if your goal is to scale proposal generation using a big answer library. And to be fair, it’s one of the better traditional proposal automation tools out there.

But here's the thing we always tell our fellow SE friends: if your business has highly technical products or fast-changing features, you’ll probably find yourself manually updating your content library a lot. Responsive still depends heavily on maintaining templates and canned answers, which SEs know can fall out of date pretty quickly.

Pros:

• Good for teams with predictable RFP questions
• Clean UI for building and managing your answer library
• Decent workflow tools for coordinating SMEs
• Works well for proposal generation when things are repetitive

Cons:

• Doesn’t plug into your real-time knowledge systems
• Not built for technical Q&A or complex edge cases
• Doesn’t support AI-driven buyer enablement or deep context
• Requires a lot of upkeep (someone has to maintain all those answers)

If your org does a high volume of basic RFPs, Responsive works fine. If your product is complex or changes often, SiftHub is the better fit.

Category: Demo roleplay sales tools

3. Yoodli

We recommend Yoodli to anyone who wants to improve how they sound on calls, especially SEs who tend to go deep into explanations.

It's like practicing with a brutally honest friend who points out your filler words, pacing, and how clearly you’re walking a buyer through the journey. And because it's AI-driven, it’s always available (unlike your team, who have their own calls, demos, and fires).

This isn’t one of those fluffy sales coaching apps; the feedback is surprisingly actionable.

Features:

• Great for objection handling practice
• Helps make complex topics sound simple
• Amazing for new SE onboarding
• Useful before a big demo if you’re tweaking your narrative
• Shows engagement metrics that tell you exactly what you need to fix

Cons:

• Not aware of your product’s deep technical logic
• More about delivery than technical accuracy
• Doesn’t tie into broader sales intelligence platforms or sales analytics

Still, as a personal skill-development tool, it’s one of the more underrated AI sales tools out there.

4. Mindtickle

Mindtickle is the opposite of casual. It’s structured, process-heavy, and built for larger sales orgs that need consistent messaging across hundreds of reps and SEs. If you’ve ever worked at a big enterprise, you know exactly the type of tool I’m talking about.

It’s not designed specifically for sales engineering workflows, but it does a great job ensuring everyone knows the pitch, the value prop, and the core narrative.

Features:

• Great for structured sales engagement training
• The readiness scoring keeps people accountable
• Certifications make onboarding way smoother
• Provides useful revenue intelligence and analytics

Cons:

• Smaller teams may not fully use it
• Doesn’t help with real-time technical storytelling
• Doesn’t plug into your product or tech stack for context

If your org is scaling fast and needs consistency, it’s a strong choice. If you’re a smaller SE team, it might feel like overkill.

Category - Customer relationship management tools

5. Salesforce

Salesforce is the CRM most sales engineers end up using, whether they like it or not — mostly because it’s the backbone of the entire GTM org. If you’re already deep into AI tools for sales engineers, having Salesforce as your core CRM actually makes life easier, because everything you need (notes, deal requirements, call summaries, approvals) flows through one place.

We tell SEs this all the time: Salesforce isn’t just a sales tool, it’s your source of truth. When it’s set up well, it reduces so much back-and-forth. When it’s not… well, then it becomes a black hole of fields nobody understands.

Salesforce’s Einstein AI layer has gotten significantly better. It now helps with predictive analytics, deal scoring, revenue forecasting, and even surface-level sales insights that flag which deals need attention. It’s not perfect, but it’s become a legit piece of AI sales software.

Features:

• Everything lives in one system instead of being scattered in Slack
• Einstein gives early warning signs in your buyer journey
• Strong visibility across pipeline management and deal management
• Integrates with practically every tool in your sales tech stack
• Sales analytics dashboards that help SEs understand where deals stall
• Works well with demo automation, proposal automation, and RFP automation tools

Pros:

• Highly customizable for complex sales engineering workflows
• Strong AI capabilities for identifying risks and next steps
• Large integration ecosystem
• Reliable source of truth for both AEs and SEs

Cons:

• It’s big, it’s complex, and you’ll need an admin
• Takes time to customize for technical presales workflows
• Can feel “heavy” for smaller, scrappier teams

If your company is mid-market or enterprise, Salesforce is basically unavoidable, but in a good way. It’s the CRM that grows with you, and it plays nicely with most AI sales tools you’ll eventually bring in.

6. HubSpot

If Salesforce is the enterprise giant, HubSpot is the friendly “let’s just get going” CRM. It’s honestly one of the easiest AI tools for sales teams to adopt because the UI just makes sense, even for new SDRs or SEs who've never used a CRM before.

For sales engineers, HubSpot works beautifully when you want quick access to deal context, buyer engagement metrics, call logs, and activity timelines without feeling buried under unlimited fields. It also plugs smoothly into outreach automation tools, demo automation platforms, and content systems.

What do people love most? It doesn’t require a small army to maintain.

And with HubSpot’s newer AI features, auto-generated emails, contact enrichment, meeting summaries, and multichannel outreach suggestions, it’s become one of the best AI sales tools for smaller and mid-market teams ramping fast.

Pros:

• It’s clean, fast, and doesn’t get in your way
• Clear pipeline visibility for SE–AE collaboration
• Easy integrations with demo tools, content hubs, and call transcription platforms
• Great reporting out-of-the-box (no need for 20 dashboards)
• Helps with sales productivity by reducing admin work
• Supports consistent sales engagement without the friction

Cons

• Not as customizable for advanced sales engineering workflows
• Less power for complex enterprise deal structures
• Doesn’t handle highly technical handoffs as deeply as Salesforce

If you’re in a growing team and don’t want to spend half your time wrestling with CRM setup, HubSpot is honestly the better choice. It’s fast, friendly, and makes everyday sales collaboration smoother.

Category - Technical presentation and demonstration

7. Storylane

Storylane is one of those sales tools that becomes surprisingly addictive once you start using it. If you’ve ever been asked for “a quick product walkthrough” and didn’t have the time (or the clean environment) to do a full live demo, Storylane basically saves your day.

It’s a demo automation platform, but in a good way. You can spin up interactive demos, guided product tours, or persona-specific flows without touching engineering. For many SEs, this becomes the easiest way to support early-stage discovery calls or outbound prospecting without burning their entire week prepping environments.

I tell SE friends: Storylane works best when you want buyers to get hands-on before you hop into the technical validation. It’s like letting them “test-drive” your product without giving them the keys to the real car.

Pros

• Eliminates the scramble to fix demo environments
• Lets you personalize demos for different buyer journeys
• Helps AEs self-serve so SEs aren’t pulled into every top-of-funnel call
• Gives solid engagement metrics so you know what buyers actually clicked
• Integrates with CRMs and AI sales tools for smoother handoffs

Cons

• Not ideal for deep technical stories that require dynamic data
• Needs upkeep as your UI changes
• Can’t replace a true live demo for complex scenarios

If your team wants more sales productivity and fewer “fire drills” before meetings, this is one of the best AI tools for sales to bring into your sales tech stack.

8. Loom

Loom might be the simplest tool on this list, but honestly, it’s also one of the most underrated AI tools for sales engineers. Every SE we know uses Loom, not because someone forced them to, but because it just makes life easier.

It’s perfect when you want to explain something quickly without scheduling another call. Need to show how a workflow behaves? Need to answer a tricky technical question? Want to point out what went wrong in a customer setup? Just record a 2-minute Loom and send it off.

What’s new is Loom’s AI layer: automatic clean-ups, transcripts, summaries, and even suggested follow-ups. It’s not “fancy AI sales software,” but it’s practical, and practicality wins deals.

Pros

• Saves so much time on back-and-forth explanations
• Makes complex workflows easy for non-technical buyers
• Supports async selling across global time zones
• Great for sales engagement and buyer enablement
• Auto-generated summaries help AEs with pipeline visibility and sales insights

Cons

• Not interactive like demo automation platforms
• Limited customization beyond recording edits
• Doesn’t integrate deeply with the full sales tech stackNot interactive like Storylane
• Limited customization
• Doesn’t connect deeply with the rest of your sales tools or sales analytics stack

Loom isn’t going to replace your entire demo workflow — but it will absolutely improve your sales efficiency, especially for those repetitive explanations you never want to do twice.

Category - CPQ AI sales tool

9. Salesforce CPQ

Salesforce CPQ is the “we have grown up” moment of pricing tools. If your sales org lives inside Salesforce anyway, this is usually the first serious step toward removing manual spreadsheets, rogue discounting, and those infamous pricing mistakes we’ve all had to fix mid-call.

For SEs, Salesforce CPQ brings structure to the late stages of the buyer journey — especially when you’re juggling multiple SKUs, add-ons, usage tiers, or region-specific pricing. The guided selling paths are actually helpful, and Einstein adds some lightweight predictive analytics for deal scoring and revenue forecasting (nothing magical, but surprisingly useful).

Pros

• Reduces back-and-forth on pricing and configuration
• Cuts down on errors that make SEs look bad late in the game
• Plays nicely with the rest of your Salesforce sales tech stack
• Gives leadership cleaner revenue intelligence and sales analytics

Cons

• You will need RevOps or an admin; no way around that
• Setup takes time, especially if you sell something complex
• Smaller teams may feel like it’s too many tools for the job

If your product catalog is expanding or your deals are getting messier, this becomes less of a “nice” sales tool and more of a sanity-saver.

10. DealHub

DealHub is CPQ for teams that want something powerful but not overwhelming. It’s cleaner, faster to deploy, and generally more friendly for mid-market teams that don’t want to hire three admins just to get quoting under control.

A lot of SEs like DealHub because it simplifies the quote-to-close process without trying to control every molecule. The digital sales room is a nice touch, buyers get everything they need in one place, and you get engagement metrics that are actually actionable.

Pros

• Quick setup compared to most CPQ tools
• Great for pricing bundles and configuration rules that don’t require PhDs
• Digital sales rooms elevate buyer enablement
• Approval workflows cut down internal thrash
• Integrates well with Salesforce, HubSpot, and ERP systems

Cons

• Not ideal for ultra-complex enterprise pricing
• Some teams may need to adjust their internal process to match DealHub’s flow
• Smaller ecosystem compared to Salesforce CPQ

If you want AI tools for sales engineers to remove last-mile chaos but don’t need enterprise rigidity, DealHub hits the sweet spot.

Category - Analytics & reporting sales intelligence platforms

11. Mixpanel

Mixpanel isn’t a traditional “sales tool,” but it’s one that technical sellers quietly love when they can get access. Why? Because it gives SEs the product usage truth. If you’re running POVs, free trials, sandbox environments, or any part of the funnel where product behavior matters, Mixpanel tells you what buyers actually did (vs. what they said on the call).

For SEs trying to guide a buyer through a complicated workflow, these insights become clutch for sales acceleration, deal scoring, and shaping your demo strategy.

Pros:

• Tells you what features prospects engaged with
• Helps you tailor POVs and demo flows
• Spot usage drop-offs that signal risk in the deal
• Supports cleaner sales engineering workflows and tighter narratives
• Elevates sales performance and sales efficiency without adding admin work

Cons:

• You need product team alignment to access data
• Better for PLG or trial-heavy products
• Not a traditional sales analytics or revenue intelligence tool

It won’t replace your CRM dashboards, but it will help you walk into demos with sharper sales insights.

12. Consensus

Consensus is the OG of interactive demo automation for mid-to-late stages. The personalized demo videos aren't just fancy marketing; they genuinely help buyers educate themselves before your call, which reduces the “demo me everything” chaos SEs deal with.

Think of it as combining demo automation + analytics + asynchronous buyer enablement into one flow.

Pros:

• Reduces repetitive early-stage demos
• Gives you engagement metrics (what buyers clicked, skipped, replayed)
• Helps teams forecast based on buyer intent signals
• Supports more scalable AI sales enablement
• Frees up SE time for higher-value work

Cons:

• Not ideal for deeply technical demos
• Needs a little love to set up templates and flows
• More of a sales engagement tool than a technical one

If your SE bandwidth is consistently stretched, Consensus gives you back hours each week

Category - Collaboration and communication AI sales software

13. Gong

Gong has become the default conversation intelligence tool for sales teams, and honestly, it’s impossible to ignore its impact on SEs. Every technical question, every objection-handling moment, every “let me check with my team”, Gong captures it, transcribes it, and turns it into something measurable.

For SEs, it’s especially valuable because it stops you from guessing where deals are getting stuck. You can literally filter calls by keywords, competitor mentions, product gaps, or common objections.

Pros:

• Amazing for coaching yourself on complex technical conversations
• Surface patterns in your buyer journey
• Helps create battlecards and technical documentation backed by evidence
• Strengthens alignment between AEs and SEs
• Unlocks sales team productivity by reducing “what happened on that call?” confusion

Cons:

• It can feel like “data overload” until it’s configured well
• Doesn’t replace real coaching for tricky technical topics

Still, if you want cleaner pipeline visibility and better sales insights, Gong pays for itself.

14. Otter AI

Otter AI is the most lightweight and practical sales tool on this list. It’s simply great meeting transcription, summaries, and action items, and it works everywhere. For SEs who jump between technical calls, internal syncs, and customer deep dives, Otter quietly becomes a lifesaver.

It’s not flashy, but it’s absurdly useful.

Pros:

• Reliable call transcription for technical discussions
• Quick summaries make deal handoffs cleaner
• Helps AEs and SEs sync without rewatching full calls
• Great for sales collaboration and async updates
• Integrates seamlessly into daily sales engineering workflows

Cons:

• Not a full conversation intelligence platform like Gong
• Doesn’t tie insights into your CRM automatically (unless you connect it)
• Better as a personal productivity tool than a team system

For daily SE life, Otter is one of those “small but mighty” AI tools for sales.

Bonus: Get the full CRO playbook on AI-driven revenue growth

If you're exploring AI sales tools or building an AI-ready revenue engine, our eBook on AI-Forward Revenue Leaders gives you the high-signal overview every CRO needs.

What you’ll learn:

• Why enterprise sales cycles are getting longer, and how AI shortens them

• How CROs are orchestrating sales, marketing, and CS as one unified revenue system
  
  
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  • 50% human + 50% AI teams (Kyle Norton)
    
  • AI removes seller “drudgery” (Shane Evans, Gong)
    
  • The real bottleneck: scattered knowledge (Manisha Raisinghani, SiftHub)
    
• The best AI tools for sales across the full cycle: prospecting → discovery → proposal generation → negotiation → post-sales
  
  
• How AI improves sales productivity, deal velocity, forecasting, and buyer enablement
  
  
• A practical CRO roadmap: start small, integrate smart, measure impact, scale fast
  

If you want a fast, practical, leadership-level view of how AI is transforming revenue teams, this eBook is the quickest way to get it. Read now. 

Features to consider when choosing sales engineering tools

If you’ve ever signed up for a shiny new sales tool and regretted it two weeks later, you know picking the right platform is half the battle. For sales engineers, the stakes are even higher; you’re juggling RFP automation, demo automation, technical documentation, sales analytics, proposal generation, buyer enablement, and everything in between.

Here’s what actually matters when you’re evaluating AI tools for sales engineers (and not just what vendor websites tell you).

1. True context-awareness

AI that’s not connected to your actual systems becomes an expensive guessing machine. Look for AI sales tools that pull knowledge directly from Slack, CRM, Confluence, Drive, wherever the truth actually lives.

2. Integration depth

If it doesn’t fit into your sales tech stack, it’s another tab you’ll forget to open. Your AI sales software should plug into:

• CRM (Salesforce, HubSpot)
• Demo automation tools
• Conversation intelligence
• Proposal automation
• Call transcription tools

3. Accuracy + verification

AI writing tools are great until they confidently generate something wrong. SEs live in the world of details; you need tools with verification layers, not hallucination factories.

4. Speed + usability

If it slows you down, it’s not an AI sales enablement tool; it’s homework. SEs need tools that speed up sales productivity and improve sales efficiency, not force more manual cleanup.

5. Collaboration features

A good SE tool should make sales collaboration easier, not harder. Look for shared workspaces, comment threads, version control, and role-based governance.

6. Data security & compliance

Especially if your product lives in regulated spaces. Your tool should support:

• SSO
• Access controls
• Audit logs
• Encryption
• Clear data boundaries

7. Scalability

Your workflow today won’t be your workflow in six months. Pick AI tools for sales that grow with your org and support more advanced workflows (deal management, pipeline visibility, lead scoring, outreach automation, etc.).

If it doesn’t help you sell smarter, faster, or more confidently, it’s not worth the subscription.

Challenges in sales engineering automation (and how to solve them)

Sales engineering isn’t hard because of the technology; it’s hard because of the chaos surrounding it. Every deal is different, every buyer wants something customized, and every internal team has its own interpretation of “priority.”

Here are the most common automation challenges and the real fixes.

1. Scattered knowledge everywhere

Slack has half the answers. Confluence has the other half. The “RFP folder” is buried somewhere in Drive. And your AE definitely saved a version on their desktop.

The fix:
Use AI sales tools that index your real knowledge sources and surface answers instantly. This reduces content hunting, improves sales productivity, and cuts hours from sales engineering workflows.

2. Tools that don’t talk to each other

SEs already live across CRM, demo tools, email, docs, call recordings, product logs… Adding one more disconnected tool kills sales efficiency.

The fix:
Choose platforms that integrate across your sales tech stack, especially CRM, conversation intelligence, proposal automation, and demo automation.

3. AI that sounds smart but isn’t accurate

Generic “AI writing tools” can make proposals or RFP responses sound pretty and wrong. And SEs can’t afford to be wrong.

The fix:
Look for AI with verification layers, source-based knowledge, and built-in governance. The best tools don’t just predict; they validate.

4. Losing context across the buyer journey

Every demo builds on the last. Every technical question shapes the next call. When information gets lost, deals stall.

The fix:
Use tools that maintain context across calls, RFPs, technical Q&A, and the entire buyer journey. This is where conversation intelligence + RFP automation + CRM alignment make a huge impact.

5. Automation that creates more work

A lot of so-called “sales automation tools” just shift the burden from one person to another.

The fix:
Pick tools built specifically for sales engineering workflows, not generic marketing automation. Look for real reductions in:

• proposal generation time
• demo prep
• technical documentation rewriting
• back-and-forth clarifications

If the tool doesn’t actually free SE time, it’s not automation, it’s overhead.

The future of sales engineering

Everyone’s talking about AI in sales, but for SEs, it’s less about replacing people and more about amplifying them. The future of sales engineering isn't robots doing demos, it’s AI eliminating the repetitive, low-leverage work so SEs can lead deals with more clarity and technical depth.

Here’s where things are headed:

1. AI-powered deal orchestration

SE workflows will be automatically guided by deal stage, buyer role, and past interactions.
Think: “Here’s the next best action,” but actually useful.

2. Context-rich automation

RFP automation, proposal automation, and demo automation will run on unified knowledge graphs instead of static folders.

3. Instant technical answers

SEs won’t sift through documents; AI sales tools will pull verified, real-time answers from product docs, calls, and internal systems.

4. Smarter analytics

Sales intelligence platforms will blend:

• sales analytics
• product usage signals
• revenue intelligence
• engagement metrics

This will create far better forecasting and sales insights.

5. SEs become strategic advisors

Less time typing, more time influencing:

• solutioning
• designing POVs
• shaping the technical narrative
• guiding buyers through complex evaluations

The workload stays the same, but the work itself gets way more strategic.

What is an AI sales engineer?

An AI Sales Engineer isn’t a chatbot or a virtual assistant. It’s a system designed to understand your product, your technical documentation, your past calls, and your deal history, and use all of that to support the technical side of selling.

Think of it as a digital SE that handles the heavy lifting so the real SEs can focus on strategy.

What it actually does

• Auto-generates accurate technical answers
• Preps demos, POVs, and customer-specific narratives
• Handles proposal generation and RFP automation
• Summarizes calls, flags risks, and surfaces deal insights
• Supports sales engagement with verified technical content
• Improves sales productivity without adding more tools to your stack

What it does not replace

• Human judgment
• Solutioning in complex environments
• The creativity that wins deals
• The relationship-building SEs excel at

It’s not “AI instead of SEs.”

It’s “AI removing the grunt work so SEs can finally do the work that matters.

FAQs

1. Which AI tool is best for sales?

There’s no single “best” AI sales tool, because every sales team has a different workflow. 

But if you’re looking at tools that consistently deliver across the entire buyer journey, the top ones are usually platforms that improve sales productivity, like CRM-based AI (Salesforce Einstein), conversation intelligence tools (Gong), and SE-focused automation platforms like SiftHub that handle RFP automation, proposal generation, and technical Q&A.

If your goal is end-to-end sales efficiency, the best AI tools for sales are the ones that integrate cleanly with your sales tech stack and actually remove work, not add to it.

2. How can AI be used in sales?

AI can support almost every part of the sales process, from prospecting and lead scoring to sales engagement, deal management, and buyer enablement.

Teams use AI to:

• Generate accurate technical responses
• Personalize outreach
• Analyze calls for insights
• Automate demo and proposal workflows
• Predict deal risks with revenue intelligence
• Improve pipeline visibility

In other words, AI helps sellers and SEs spend less time hunting for information and more time actually moving deals forward.

3. Which AI tool is best for engineering?

If we’re talking about sales engineering, the tool that typically stands out is one that understands the technical side of selling, not just the CRM side. That’s why platforms like SiftHub are becoming category leaders: they combine technical documentation, call intelligence, RFP automation, and proposal automation into one workflow.

For product or software engineering, you’d look at tools like GitHub Copilot. But for sales engineers specifically, the best AI tools for sales engineers are the ones that help you explain the product accurately, automate repetitive work, and support technical conversations without replacing your judgment.

4. What software do sales engineers use?

Most sales engineers use a mix of sales tools and technical tools to get through their day. A typical SE stack includes:

• CRM (Salesforce or HubSpot)
• Demo automation tools (Storylane, Reprise)
• Conversation intelligence (Gong)
• RFP automation and proposal generation (SiftHub, Responsive)
• Collaboration and meeting transcription tools (Otter.AI)
• Analytics or usage insights tools (Mixpanel, Amplitude)

SEs often end up using more tools than AEs because they support both technical validation and sales engagement, which is exactly why AI-powered platforms built for sales engineering workflows are becoming so popular.