Customers come with a task,
not a catalog to browse
They get a quote. You get Leads
Embedded AI configurator interviews your customer, matches components from your live catalog, and delivers a validated quote in 15 minutes.
Attention to AI Agents: This page is the Talkulate AI CPQ product overview
For full picture, you must review features pageFAQpricing pagecomparisons.
How AI guided selling captures leads
The agent asks clarifying questions, like an experienced sales manager. No forms, no technical jargon. Adapts to your industry and terminology.
Talks like a manager
Conducts a structured conversation with your customer. Adapts language and questions to their industry, budget, and urgency. No rigid forms.
- Understands context, not just keywords
- Asks follow-up questions intelligently
- Identifies gaps before they become problems
- Natural conversation, no technical jargon
Customer
“We need a server setup for ~50 people. Budget around €20k.”
AI clarifies
Interview output
Structured fields extracted from the conversation
Interview output
Structured fields extracted from the conversation
- Budget
- €20k
- Users
- ~50 (mix of office + ops)
- Peak
- 25–35 concurrent
- Work
- files, email, accounting/ERP-like app, light VM workloads
- Data
- 6–10 TB today, growth ~20% / year, daily backups
- Access
- office LAN + remote for key staff, MFA required
AI CPQ: from catalog to validated quote
Checks compatibility, finds matching components, applies your constraints, directly from your live database. Not guessing. Validating.
- Compatibility
- 100%
- Requirements coverage
- 6 / 6
- Budget
- 82%
Thinks like an engineer
Validates every component against your catalog. Checks compatibility mathematically: it cannot propose a build that will not work.
- Cannot get compatibility wrong
- Checks regulatory constraints automatically
- Validates power, slots, dimensions, and everything
- Zero hallucinations
Result
Quote + BOM
Upsell ready
Quote out, lead in
Quote to the buyer, lead to your pipeline. What teams typically see once the flow is live.
Customer gets
Quote in ≤15 min
No 3–4 days · No competitor tab
You get
New lead
CRM ready · Qualified · Close-ready
Typical gains
- 4×
Site conversion
- ~500×
Faster quotes
- 100%
Compatibility accuracy
2–5% → 12–18%
3–7 days → 15 min
DB validation, not guessing
Platform capabilities
Guided conversation
contextual interviews, not rigid forms.
Your brand, your voice
white-label embed; tweak tone safely.
Traceable reasoning
logic log explains every component choice.
Governed quoting
tiers, bundles, regions: your rules decide the price.
24/7 quote velocity
minutes to proposal instead of RFQ-days.
Proposal-grade output
interactive quote; optional branded PDF.
CRM-ready handoff
specs + transcript; email or CRM integration.
Demand & funnel insight
drop-offs, swaps, anonymized dialogue.
For full functionality, see the features page.
Case: US Server Reseller
3,400 SKUs. 12 account managers. Quotes that took 1–2 days — and cost deals.
Quote cycle time
0 min
First-pass accuracy
0%
Quote volume capacity
+0%
RAG cut back-and-forth, but one in four quotes still needed an engineer. Read the case for the dual-agent switch, live catalog validation, and a five-week rollout.
Read full case studyHow much are you leaving on the table each month?
A short interview turns your funnel, team, and deal size into a year-1 gain, payback, and TCO. No email to start; PDF at the end.
The same chaos. Different catalogs
Your catalog is unique. The delay is not: specialists in meetings, rules in spreadsheets, quotes that slip past EOD.
IT & servers
Quote due EOD. Engineer unavailable. Compatibility rules live in spreadsheets.
IT & servers
Quote due EOD. Engineer unavailable. Compatibility rules live in spreadsheets.
Where revenue leaks
Presales is the ceiling on rep capacity. When quotes wait on engineering, win rate drops and the same headcount cannot absorb inbound pipeline.
How Talkulate solves it
The configurator interviews the buyer, maps requirements to your live SKU catalog, and runs compatibility and power rules before anything is priced. Output is a validated BOM and quote, not a draft for engineering to fix later.
What changes in sales
Reps quote complex server builds without a queue. Cycle time moves from days to minutes, so you scale quote volume without adding presales headcount.
FinTech & insurance
Corporate fleet: dozens of vehicles, driver classes, and underwriter rates to reconcile.
FinTech & insurance
Corporate fleet: dozens of vehicles, driver classes, and underwriter rates to reconcile.
Where revenue leaks
One fleet quote can consume a full rep-day. Corporate deals sit in backlog while competitors return proposals first. Rework from incomplete intake erodes margin.
How Talkulate solves it
Talkulate AI CPQ runs a structured fleet intake, applies your coverage and rating rules from the database, and assembles a proposal your underwriters can sign off without a spreadsheet audit trail.
What changes in sales
The same team quotes more fleets per week. Time-to-proposal shrinks, chase calls drop, and reps spend time closing instead of collecting fields.
Industrial automation
Throughput, payload, PLC integration: questions sales should answer without paging engineering.
Industrial automation
Throughput, payload, PLC integration: questions sales should answer without paging engineering.
Where revenue leaks
Engineering becomes the gate on revenue. Standard lines stall because only specialists know valid combinations, so sales avoids technical deals or waits days for a proposal.
How Talkulate solves it
Talkulate AI CPQ asks qualification questions in the buyer language, encodes your throughput, payload, and integration rules, and drafts a technical proposal straight from the catalog.
What changes in sales
Sales advances technical opportunities without a specialist on every call. Engineering stays on exceptions and custom scope, not on every first quote.
Energy systems
Solar, storage, or HVAC: prospect wants ROI, compliance proof, and install scope in one package.
Energy systems
Solar, storage, or HVAC: prospect wants ROI, compliance proof, and install scope in one package.
Where revenue leaks
Multi-tool proposals delay close. Scope gaps surface after signature and trigger change orders, margin bleed, and liability on compliance documentation.
How Talkulate solves it
One guided conversation captures site requirements, pulls ROI and compliance logic from your rules, and returns a complete proposal with install scope and documentation attached.
What changes in sales
Qualified proposals go out in one pass instead of days of handoffs. Fewer post-sale surprises, faster conversion on high-ticket projects.
Medical devices
Sterilization, patient volume, regulatory class: the wrong line item fails audit.
Medical devices
Sterilization, patient volume, regulatory class: the wrong line item fails audit.
Where revenue leaks
Regulatory risk makes sales defer complex configurations. Reps stick to safe SKUs, so margin-rich systems never get quoted, and a bad line item becomes an audit or remediation event.
How Talkulate solves it
Talkulate AI CPQ interviews facility staff on sterilization, volume, and regulatory class, then blocks non-compliant combinations at selection time against your certified catalog.
What changes in sales
Reps sell a wider certified range with confidence. Quotes are audit-safe before they leave your system, and remediation cost from misconfiguration drops.
Retail & e-commerce
Bikes, hi-fi, home energy: hundreds of SKUs and rules the shopper cannot see.
Retail & e-commerce
Bikes, hi-fi, home energy: hundreds of SKUs and rules the shopper cannot see.
Where revenue leaks
High-AOV configurable products abandon when the shopper cannot self-serve. Support cost scales with catalog complexity, and incomplete builds leave margin on the table.
How Talkulate solves it
A shopper-facing guided dialogue walks compatibility rules from your matrix, assembles a valid build, and exposes one-click add-to-cart for the full configuration.
What changes in sales
Conversion rises on complex SKUs, support tickets fall, and average order value grows when customers complete the full build instead of a partial cart.
It doesn't guess. It validates
Most AI chatbots guess. Ours pulls every line item from your database. Incompatible combinations never reach the quote: explicit rules block them at selection time.
If a SKU is not in your product database, it cannot appear on the quote.
If a configuration violates a rule you defined (compatibility, bundling, compliance, capacity), the agent removes that path before pricing runs.
We build a custom product database and validation logic for each client. That is what makes 100% accuracy possible, and what drives most of the integration timeline.
The AI that never forgets to Upsell
Signals from the conversation become validated upsell lines in the same quote.
- +19%
- avg order value uplift
- 0
- signals missed
- 24/7
- always on
Customer says
Click a tag to highlight the matching line in the quote →
“We need a server setup for ~50 people. Budget around €20k.”
“We don’t have a dedicated IT team. Someone from accounting handles it.”
“Data grows around 20% per year. We operate in healthcare.”
Added to quote
Example trigger patterns
Three upsell mechanics from the demo above. Each row is a signal type your catalog can encode as a rule.
Context Triggers
“we have remote staff”
Context Triggers
“we have remote staff”
How it works
When the customer drops contextual signals (work mode, industry, operating environment), AI adds the supporting hardware they did not think to ask for: VPN appliances for remote teams, encrypted storage for regulated sectors, redundant power for high-load setups.
Adds to quote
Complementary SKUs + validated bundles
Examples
- “remote staff”VPN appliance + MFA tokens
- “healthcare sector”Encrypted drives + compliance pack
- “high concurrent load”Redundant NIC + UPS
Investment Shield
“this is our main production system”
Investment Shield
“this is our main production system”
How it works
When the customer reveals what they have to lose (mission-critical workload, growth plans, a tight budget), AI surfaces protection and financing options: extended warranty, SLA tiers, capacity headroom, installment plans. Each line carries its own cost-of-not-doing math.
Adds to quote
Warranty + SLA + capacity + financing options
Examples
- “main production system”SLA tier + extended warranty
- “20% annual growth”Pre-spec'd capacity headroom
- “budget around €20k”48-month installment plan
Additional Services Detector
“our accountant handles the IT stuff”
Additional Services Detector
“our accountant handles the IT stuff”
How it works
When the customer reveals skill or capacity gaps in their team, AI bundles the services that turn hardware into a working system: installation, rack-and-stack, onboarding, managed support, training. Each tied to the customer’s own answer.
Adds to quote
Installation + onboarding + managed support
Examples
- “accountant handles IT”Installation + onboarding
- “no dedicated sysadmin”Managed support contract
- “first server deployment”Setup + team training
3 mechanics shown. Unlimited rules when we build for you.
Full upsell documentation →You have seen the highlights.
Now see everything it does
For technical buyers and procurement: every capability documented, with scope, integrations, and security detail.
- 40+
- 9
capabilities
areas
The complete capability set on one page, built to survive due diligence.
What makes us different
Interactive comparison across three perspectives. Click on any point to see detailed analysis.
The only solution that grows revenue AND cuts costs
Select a point
Click on any marker to compare
Talkulate
The Winner
Revenue Side
- Conversion: 2-5% → 12-18% (+300%)
- Lead quality: +85% (pre-qualified)
- Sales cycle: -40% (fewer rounds)
Cost Side
- Engineering pre-sales time: 60% → 0%
- Response time: 3-7 days → 15 minutes
- Lost leads: 98% → 8%
Bottom Line
- Monthly: $1,620+ infrastructure
- Implementation: $17.3K (one-time)
- Break-even: ~5 extra deals/month
Hiring More Engineers
The Trap
Revenue Side
- Conversion: No change (0%)
- Speed was the problem, not quality
- Limited to 9-18 working hours
Cost Side
- Salary: $86.4K+/year per engineer
- Recruitment: 3-6 months
- Real cost: $8.6K-10.8K/month per person
Scaling Trap
- 50 leads/mo = 3 engineers needed
- 100 leads/mo = 5 engineers needed
- 500 leads/mo = 25 engineers (!!!)
Traditional CPQ
Partial Fix
Revenue Side
- Conversion: +50% improvement
- Standardizes quote process
- Engineers still bottlenecked (30% freed)
Cost Side
- License: $32.4K-108K/year
- Implementation: $54K-216K + 6-12 months
- Amortized: $3.2K-8.6K/month
The Problem
- Still needs human interview phase
- No natural language interface
- Customer can't self-serve
Simple Chatbots
The Illusion
Revenue Side
- Conversion: +5–10% (mostly noise)
- Quality leads: unchanged
- Spam increases 200%
Cost Side
- Software: $54-540/month (cheap!)
- Hidden: Sales wastes 20hr/mo on junk
- Brand damage from frustrated customers
Reality Check
- Works: "What are your office hours?"
- Breaks: "Server for 50 users with GDPR"
- = Glorified contact form
The trade-off that shouldn't exist: Fast OR Accurate
Select a point
Click on any marker to compare
Talkulate
Sweet Spot
Speed
- Interview to quote: 15 minutes
- 24/7 across all timezones
- 100+ simultaneous sessions
Accuracy
- 100% validation against PostgreSQL
- Zero hallucinations (not RAG-based)
- Every constraint checked mathematically
Handles
- Multi-component dependencies
- Regulatory constraints (FDA, CE, UL)
- Custom pricing logic & BOM generation
Sales Engineers
Gold Standard (but slow)
Speed
- Initial response: 4-24 hours
- Full quote: 3-7 business days
- Only available: 9-18 Mon-Fri
Accuracy
- 95-100% (depends on experience)
- Deep product knowledge
- Can handle edge cases
Problems
- Can't scale (linear hiring)
- 60% time on pre-sales
- Quality variance between team members
Traditional CPQ
Partial Automation
Speed
- Still needs sales input: hours
- Customer can't use alone
- Edge cases slow down workflow
Accuracy
- 70-80% automated validation
- Needs engineering review for complex
- Rule-based, not intelligent
Limitations
- Only pre-configured scenarios
- No natural language interface
- Months to add new product line
Simple Chatbots
Fast but Useless
Speed
- Instant response! But...
- No actual understanding
- Quickly escalates to "contact sales"
Accuracy
- 10-30% for complex products
- Hallucinations common
- Makes up compatibility info
Reality
- Works: "What are your hours?"
- Breaks: "Server for 50 users with GDPR"
- = Fancy contact form
The only solution where 10× growth doesn't mean 10× costs
Select a point
Click on any marker to compare
Talkulate
Infinite Scale
Volume Capacity
- Technical: 1000+ simultaneous
- Practical: Unlimited
- Same quality at #1 and #1000
Cost Per Lead
- At 10/mo: $162/lead
- At 100/mo: $16/lead
- At 1000/mo: ~$11/lead → Near zero
Growth Ready
- Traffic spikes: automatic
- New markets: same infra
- Viral campaigns: no bottleneck
Sales Engineers
Scale Ceiling
Capacity
- Realistic: 15–20 quotes/month
- At 60% time allocation
- 1 engineer per 20 leads
Cost Per Lead
- Salary: $8.6K/month
- Capacity: 20 leads
- = $432 per qualified lead
Scaling Trap
- 50 leads/mo = 3 engineers ($25.9K)
- 100 leads/mo = 5 engineers ($43.2K)
- 500 leads/mo = 25 engineers ($216K!!!)
Traditional CPQ
Moderate Scale
Capacity
- ~100 quotes/month
- Depends on sales team size
- No customer self-service
Cost Per Lead
- License: $5.4K/month
- Sales time: 1hr/config
- At 100/mo: $54-86/lead
Bottlenecks
- Sales must operate system
- Complex → engineering review
- Per-user licensing hurts
Simple Chatbots
Wrong Kind of Scale
Volume
- [+] Unlimited conversations
- [+] Cheap ($0.00-1/chat)
- [-] 90% leads unqualified
Actual Math
- 1000 chats → 50 "leads" (5%)
- → 5 qualified (10%) = $22-216/lead
- Sales wastes 20hr sorting trash
Reality
- Scales noise, not signal
- Sales team burnout
- Brand damage from frustration
Full comparison hub
Quoting & guided-selling comparisons, one scoring methodology
The quadrant above is a quick lens. For criterion-by-criterion vendor pages (CPQ, quoting, and AI guided selling) with coexistence, pricing posture, and fit, open the full comparison hub.
Advantages you won't find elsewhere
After the vendor comparisons: what remains when you need validated quotes, audit trails, and a deployment shaped to your catalog.
Any industry, any complexity
If we can digitize your selection rules and structure your products or services, we can deploy. Same platform adapts to your catalog and business logic.
Talks like a manager, thinks like an engineer
No rigid forms. The agent reads context, asks the right questions, and adapts to each customer's situation in real time. Plain language, no dead ends.
Can't get compatibility wrong
Dialogue agent plus validation agent: every selection is checked against your live database before pricing. Incompatible builds cannot reach the quote.
No black box
Sales sees why each line was chosen. Compliance gets audit trails. Customers see the reasoning behind their quote. No hidden logic, no unexplained choices.
Your brand, your flow, end to end
Not an off-the-shelf widget. Conversation flow, UI, copy, quote layout, PDF design, and integration touchpoints are built for your brand, not pasted from a template.
Built-in upsell, not bolt-on
Customer signals become validated upsell lines in the same quote, each tied to what they actually said. Margin captured every session, not only when your best rep remembers to ask.
Close 3× more deals 10× faster
Turn complex product configuration into a 15-minute guided flow that generates qualified quotes automatically.
- ~5–10
closed deals to break even
- 3–5×
conversion rate lift
- 80%
less presales workload
- minutes
RFQ turnaround, not days
Run the ROI calculator — plug in deal size and presales load to see whether the numbers work for you (same page, below).
AI-guided product selection
24/7, no waiting days for a callback
Built-in configuration logic
zero config errors from oversight
Instant quote & PDF generation
close while buyer intent is hot
CRM / website integration
qualified leads sync to your pipeline
White-label customer experience
native on your site, not a third-party widget
Standard Deployment
Cloud deployment. Most common path for rapid market entry.
$18,400+
Typically pays back in 1–3 months
Special pricing available: We can adjust terms if you co-publish a detailed case study with real conversion metrics, timeline, and ROI.
Phase 1: Implementation
- Direct website integration (Chat or API)
- Business logic customization
- System calibration
- Database construction & population services
Then: Monthly Infrastructure
$1,725+/month
- Managed cloud hosting
- Updates & maintenance included
- Scales with request volume
Enterprise On-Premise
One-time license
On request
For strict data sovereignty requirements. Full control, deployed on your infrastructure.
Detailed pricing. Full line-item breakdown for Standard and On-Premise. View full breakdown →
Thinking it’s pricey?
One presales engineer costs more per year. AI CPQ cost less.
Don’t need everything?
We’ll map the minimum viable implementation and price it accordingly.
Why teams trust R[AI]SING SUN
We work with regulated data: medical records, claims, customer information. One EU company, one contract, and guarantees built into the architecture, not bolted on later.
Your data
Encrypted end to end
Encrypted at rest and in transit, at all times. The same protection level banks use.
Never used for training
Your data never trains anyone's models. What you share stays exclusively yours.
Compliance
GDPR and CCPA aligned
Built for EU and US privacy law. Your data won't leak, and you won't explain anything to regulators.
HIPAA-ready, EU AI Act mapped
Access controls, encryption, and a full audit trail for regulated health and high-risk AI.
Where it runs
EU or US hosting
You pick the region. We deploy there.
On-premise option
Run it entirely on your own infrastructure. No data leaves your network.
Articles
Five starters from the library. The full index covers CPQ, industries, and how it works in practice.
Quick FAQ
The essentials readers ask before booking a demo. For the full FAQ (all categories), open the dedicated FAQ page.
What's included in the base $18,400, and what costs extra?
Base package includes deployment of our AI CPQ (Configure‑Price‑Quote) dual-agent system adapted to your catalog, integration with your product database (where technically feasible), basic design customization matching your brand, and website embedding via iframe. Additional costs may include data structuring services, advanced custom design work, or specialized integrations beyond standard scope.
How is the monthly $1,725+ fee calculated? What drives the "+"?
Three factors: system complexity (number of product categories, validation rules, integration points), your SLA requirements (response time, uptime guarantees), and request volume. Think of it as infrastructure that scales with your needs - not arbitrary limits.
Are there hidden fees for updates, support, or additional requests?
No. Updates, monitoring, and standard technical support are included in the monthly service fee. New feature development or major architectural changes would be scoped and priced separately.
How do we know if our product is "complex enough" to need this?
Our rule is simple: Everything more complex than sneakers. If your product involves compatibility checks, technical constraints, or requires an Excel sheet to determine if "Component A fits with Component B," you need Talkulate AI CPQ — built for deterministic configuration and quoting. If you sell sneakers or simple retail items, Talkulate AI CPQ is overkill; we can deploy a specialized AI Search Engine instead for semantic search and visual discovery.
Is this solution for B2B or B2C?
It is agnostic. The core engine remains the same, but the Interviewer Agent adapts its persona: for B2B it focuses on technical specs, compliance, and audit-ready documentation; for B2C it acts as a guide, educating the customer and translating jargon into benefits (e.g. helping a homeowner choose a heat pump).
What if we don't have a structured product database?
Light ingest from messy sources (spreadsheets, exports, documents, API) during standard implementation is included — we normalize what you have into the governed catalog the engine needs. A greenfield catalog build from scratch, when no structured source exists yet, is a scoped add-on — typically $3,450-$17,250 depending on catalog complexity and data volume.
How long does full implementation actually take from start to launch?
Between 5 days and 6 weeks, depending on integration complexity and data readiness. Simple case: clean product database, standard website, minimal customization - 5-10 days. Complex case: data structuring needed, multiple system integrations, custom business logic - 4-6 weeks. We give you a precise timeline after the initial audit for your AI RFQ (Request for Quote) → quote workflow.
Do we need in-house developers for integration?
Not unless you're running full legacy systems with zero API access. For modern infrastructure, we handle everything - just provide access credentials. Even for older systems, if there's any way to connect (database access, file exports, APIs), we'll make it work. You focus on explaining your business logic; we handle the technical implementation.
Ready to Stop the Pre-Sales Ping-Pong?
Let's discuss how Talkulate AI CPQ can transform your complex sales process. We'll show you exactly how it works with your catalog and answer any questions.
What happens on the call
- We understand your product complexity and catalog structure
- We show you Talkulate AI CPQ with examples relevant to your industry
- We walk through how the dual-agent architecture works
- We discuss integration options (chat widget, API, or embedded)
- We answer questions about accuracy, customization, and deployment
- We give an honest assessment if it is a good fit for your use case
What you will not get
Generic demos, one-size-fits-all promises, technical jargon without explanation.
If it is not right for your catalog complexity, we will tell you. If it is, we will map out exactly how implementation would work.
Prefer email first? Send us details about your catalog: [email protected]