What a Digital Customer Experience (CX) Platform actually does
Extracts themes from customer feedback, generates closed-loop responses, and surfaces sentiment trends across channels.
A white-label CX platform sits at the intersection of feedback collection (NPS, surveys, reviews, social mentions), theme extraction (what are customers actually saying?), and orchestration (auto-respond to detractors, escalate critical issues). The architecture combines a survey/feedback intake layer with LLM-powered thematic analysis and a response-template engine. Paragraph 2: The global CX platform market is $2.1B annually (Sprinklr, Qualtrics, Medallia dominate), but these players target enterprises at $50K+/yr—leaving an open lane for consultancies serving SMB SaaS clients who want a branded NPS + closed-loop platform at $99–$249/mo. Claude Sonnet 4.6 with prompt caching makes high-volume feedback analysis (1,000+ items/mo) economical—theme extraction costs drop to <$5/mo even at scale.
AI capabilities involved
Theme extraction from open-text feedback
Sentiment classification and trend analysis
Auto-drafted closed-loop response generation
Embeddings for theme clustering
Who uses this
- CX consultancies and VoC (Voice of Customer) program managers serving 5–20 mid-market SaaS clients
- Fractional Chief Customer Officers bundling NPS + sentiment dashboards as a service
- Customer Success–as-a-Service firms selling retention-focused analytics to product companies
- Customer feedback agencies positioning against legacy Qualtrics deployments with a 90% cost reduction
SaaS alternatives on the market
Real products you can sign up for today — with current 2026 pricing, honest pros and cons.
Qualtrics XM Platform
Large enterprises (500+ FTEs) with complex regulatory requirements who want an all-in-one platform and have IT support to manage integrations
14-day trial
$1,500+/mo (enterprise quote)
$5,000+/mo and up
Pros
- +Multi-channel feedback integration (NPS, CSAT, CES, open-text, social)
- +Advanced segmentation and journey analytics; drill-down into cohorts by product feature, cohort, geography
- +XM Directives (AI-assisted reporting) for automated insight generation
- +Market-leading compliance: SOC 2 Type II, HIPAA BAA, GDPR DPA in every package
Cons
- −Enterprise-grade pricing ($1.5K–$5K/mo) makes reseller margin impossible
- −Learning curve: UI requires training; no agency-tier white-label rebrand available
- −Feature bloat: CX/EX/CS/HR/Product all bundled—you pay for modules your clients won't use
- −Lock-in on responses: closed-loop features are proprietary to Qualtrics; data export complexity
Sprinklr Customer Experience Cloud
Large enterprises with >1,000 support tickets/day who need omnichannel routing and can afford 6-month contract minimums
None (enterprise sales only)
$2,000+/mo (estimated minimum for SMB tier)
$5,000–$50,000+/mo
Pros
- +Omnichannel orchestration (email, SMS, social, chat) unified in one platform
- +AI-powered routing and auto-response via Sprinklr AI Agent
- +Real-time sentiment and theme extraction across all channels
- +SOC 2 Type II + HIPAA BAA support
Cons
- −Vendor lock-in: data trapped in Sprinklr's proprietary sentiment model
- −Pricing opacity: you need an enterprise sales call to get a quote; no self-serve SMB tier
- −No white-label; reseller program requires $100K+ annual commitment
- −Response SLA: auto-generated responses often need 20–30% manual review (model hallucinations)
Formbricks (Open-Source NPS + Survey)
Consultants willing to self-host on a Hetzner/Railway VPS and add a thin AI sidecar (Lovable) for theme extraction; targets 5–15 mid-market clients at $99/mo
Self-host OSS (free, 50K stars on GitHub)
$30/mo (Cloud, Basic plan)
$500+/mo custom
Pros
- +True white-label via self-hosting (Docker on Hetzner $5/mo VM)
- +No limits on survey responses or users (self-hosted)
- +Fast API for programmatic survey creation and response ingestion
- +Community + commercial support for custom integrations
Cons
- −Survey-only; no built-in sentiment analysis or theme extraction—you layer that via API calls
- −Admin UX behind Notion/Qualtrics (learning curve for non-technical clients)
- −Limited pre-built integrations vs. Qualtrics (you'll build custom Zapier/n8n workflows)
- −Data residency: you manage backup/GDPR compliance yourself when self-hosting
The AI stack
A production CX platform requires three layers: feedback intake (surveys, API ingestion), LLM-powered analysis (theme extraction, sentiment scoring), and response orchestration. The cost-quality tradeoff: use Sonnet 4.6 with prompt caching for theme extraction (90%+ accuracy, $0.005 per 100-item batch), DeepSeek V4 Flash for high-volume sentiment classification (<$0.0001 per item), and Voyage embeddings for clustering similar themes.
Feedback Intake & Normalization
Collect NPS, CSAT, surveys, and ingest from third-party APIs (Slack, Zendesk, email); standardise to a common schema
Supabase PostgreSQL + pgvector + Webhook ingestion
$25/mo Supabase Pro (100GB storage, 2M API calls)Teams with SQL comfort; can write custom integrations for Zendesk, Slack, etc.
Formbricks self-host (feedback intake only)
$5/mo Hetzner VM + $0 softwareConsultants who want to own the intake UX and don't mind DevOps overhead
Our pick: Supabase Pro ($25/mo) for production (multi-client, audit logs, backups included); Formbricks self-host for agencies wanting full white-label intake UX and willingness to manage infrastructure.
Foundation Model: Theme Extraction & Sentiment
Analyse 1,000s of feedback items for dominant themes, sentiment classification, and topic clusters
Claude Sonnet 4.6 with prompt caching
$3/$15 per M tokens input/output; caching reduces effective cost 90% on repeated document analysisBatch processing feedback at week/day cadence; high accuracy required (healthcare, fintech contexts)
DeepSeek V4 Flash
$0.14/$0.28 per M tokens input/outputHigh-volume customers (>10K feedback items/mo); when accuracy 75%+ is acceptable
Claude Opus 4.8
$5/$25 per M tokensHigh-stakes contexts (healthcare feedback, legal discovery, executive summaries) where errors carry regulatory risk
Our pick: Default to Sonnet 4.6 with caching for theme extraction (90% accuracy, $0.005 per 100-item batch). Add Opus 4.8 layer for high-stakes summaries (CEO/board-facing reports). Use DeepSeek V4 Flash for high-volume sentiment tagging on >10K items/mo (reduce per-item cost to <$0.0001).
Embeddings: Theme Clustering & Similarity
Group similar themes together, retrieve past responses to similar feedback, surface semantic trends
text-embedding-3-small
$0.02/M tokensMost use cases; balances cost and accuracy
text-embedding-3-large
$0.13/M tokensHealthcare or legal discovery (where theme classification errors carry risk)
Voyage voyage-3.5
$0.06/M tokensTeams needing RAG (retrieve past responses to similar feedback) with moderate cost sensitivity
Our pick: text-embedding-3-small ($0.02/M) for basic clustering; upgrade to Voyage voyage-3.5 ($0.06/M) if implementing RAG (retrieve past customer responses for similar feedback patterns).
Closed-Loop Response Generation
Draft personalised responses to detractors (NPS <7), auto-generate thank-you messages to promoters (NPS 9–10), escalate critical feedback
DeepSeek V4 Flash
$0.14/$0.28 per M tokensTemplate-heavy responses (thank-you sequences, standard apologies); high volume (1K+ responses/mo)
Claude Sonnet 4.6
$3/$15 per M tokensTier-1 customers (high-value accounts); executive-level feedback responses
Our pick: Default DeepSeek V4 Flash for high-volume auto-responses (thank-yous, standard apologies) at <$0.0001/response. Route high-touch accounts (top 10% by ARR) through Sonnet 4.6 for personalised responses that reference past interactions.
Reference architecture
The pipeline: survey response lands in Supabase → Webhook fires → Edge Function ingests into pgvector → batch-process feedback 1x/day via Sonnet 4.6 with prompt caching to extract themes → embeddings cluster themes in pgvector → theme summary + sentiment → Voyager API retrieves similar past responses → generate closed-loop response draft (DeepSeek for volume, Sonnet for high-touch). The hardest part: handling feedback volume spikes (post-campaign, post-incident) where queued items back up; use Trigger.dev or Inngest background jobs to prevent Edge Function timeouts.
Customer submits NPS response + open-text feedback via branded Formbricks form or direct API call
Formbricks (intake) or Supabase Edge Function (API)Feedback record stored in Supabase with client_id, user_id, nps_score, text, created_at. Webhook fires immediately to ingest function.
Ingest function normalises feedback (extract language, validate NPS 0–10 range, flag sensitive PII for masking)
Supabase Edge Function (Node.js, 60 sec timeout)Runs regex to detect email addresses, phone numbers; masks PII with [REDACTED]. Stores normalised record in feedback table with metadata.
Daily batch-process job (1 AM UTC) triggers Sonnet 4.6 to extract themes from unbatched feedback
Trigger.dev or Inngest scheduled job → Sonnet 4.6 via Anthropic APIQuery last 24h of feedback_table, chunk into 100-item batches, send to Sonnet with cached prompt template (90% cache hit rate on recurring customers). Sonnet returns theme array + per-item classification.
Store theme + embeddings in pgvector; cluster similar themes via cosine similarity
Supabase pgvector + text-embedding-3-smallGenerate embeddings for each theme, insert into theme_embeddings table with similarity search. Daily cluster report: 'Top 5 themes this week: price (28%), speed (22%), support (18%), …'
For each NPS <7 (detractor), retrieve similar past feedback via vector similarity, draft response using past response as template
Voyage voyage-3.5 embeddings + DeepSeek V4 Flash (or Sonnet 4.6 for top-tier clients)Cosine similarity on embedding of current feedback → retrieve top 3 past similar items → feed to LLM with instruction 'Draft a response that matches the tone of these past responses but addresses {current_feedback_summary}' → generate draft and store in response_drafts table.
CX consultant reviews and approves draft, marks as sent or edits and sends manually
Supabase + Next.js front-end (dashboard)Dashboard shows pending detractor responses sorted by NPS score (lowest first). One-click approve sends via email/SMS integration (Sendgrid/Twilio).
Estimated cost per request
~$0.005 per 100-item theme batch (Sonnet 4.6 with caching, ~40K input tokens + 2K output @ $3/$15 per M with 90% cache hit). ~$0.00015 per detractor response draft (DeepSeek V4 Flash, ~200 in + 300 out). Total cost per customer per month at 500 feedback items/mo: ~$0.35 (themes) + ~$0.50 (response drafts) = ~$0.85 LLM COGS.
Cost calculator
Drag the sliders to model your actual usage. The numbers update in real time so you can stress-test economics before writing a single line of code.
This calculator models the monthly LLM + infrastructure cost to run a white-label CX platform for mid-market SaaS customers. Assumptions: each customer submits 500–5,000 feedback items/mo via NPS surveys. Deployment covers Supabase, Sonnet 4.6 with caching, embeddings, and response drafting. No seat-based pricing—one flat $99–$249/mo per customer.
Estimated monthly cost
$90.01
≈ $1,080 per year
Calculator notes
- Sonnet caching assumes 90% cache hit on repeated prompts (weekly theme extraction uses same system prompt; saves 90% of input token cost).
- Detractor percentage varies by industry: B2B SaaS typically 25–35%, consumer 15–30%, healthcare 35–50%.
- Cost per feedback assumes batching: daily batch of 100 items = 1 API call, not per-item calls.
- Not included: your labour (reviewing drafts, editing responses), affiliate fees if reselling Formbricks, or customer-success overhead (onboarding, support tickets).
Build it yourself with vibe-coding tools
A white-label NPS + theme-extraction MVP can run by Sunday night—Lovable scaffolding + Sonnet 4.6 caching + pgvector clustering. You'll have a multi-tenant dashboard where you upload client data, bulk-generate themes, and export response drafts. Not production-grade (no auth per-client, limited compliance), but enough to test the market with 3–5 early customers.
Time to MVP
12–16 hours (one weekend)
Total cost to MVP
$25 Lovable Pro + ~$30 Sonnet/embedding API credits
You'll need
Starter prompt
Build me a white-label CX feedback analysis app. Here's what I need: 1. Data ingestion: One CSV upload modal where I paste feedback items (client_id, nps_score, text). Store in Supabase. 2. Bulk theme extraction: After upload, I click 'Analyse' and the app calls Claude Sonnet 4.6 to extract themes from the text. Show me 5–10 detected themes per analysis with a confidence score (e.g., 'Price complaints (28%, confident)', 'Speed issues (15%, moderate)'). 3. Embeddings clustering: After theme extraction, cluster similar themes using Voyage embeddings stored in pgvector. Show me a visual: 'Top 5 theme clusters this week'. 4. Response drafts: For each NPS <7 feedback item, auto-draft a response using DeepSeek V4 Flash. Show a list of drafts with a checkbox to approve. 5. Export: One-click export of approved responses as a CSV (client_id, original_feedback, draft_response, status). UI: Sidebar nav (Upload / Analyse / Themes / Drafts / Export). Dark theme, Tailwind. Use Supabase Auth for multi-tenant isolation (email + password). RLS rules: each client can only see their own feedback. Use Supabase Edge Functions for API calls to Sonnet and Voyage to avoid exposing keys.
Paste this into Lovable
Follow-up prompts (run in order)
- 1
Add a 'Sentiment Dashboard' page: bar chart showing NPS distribution (0–10) by day this month, and a stacked bar of positive/neutral/negative sentiment over time.
- 2
Implement prompt-caching for Sonnet 4.6: on the second analysis run with the same client, the app should re-use the cached theme-extraction prompt (90% cost savings on input tokens).
- 3
Add Sendgrid integration: 'Send Responses' button that auto-populates a Sendgrid draft for each approved response, pre-fills the client email from the feedback record.
- 4
Add a feedback-search feature: given a new feedback item, find the 3 most similar past items using vector similarity (cosine distance on Voyage embeddings).
- 5
Compliance layer: before storing feedback, mask email addresses and phone numbers with [REDACTED]; log all theme extractions (timestamp, user, customer_id, themes) for audit trails.
Expected output
By Sunday: a working multi-client feedback-analysis dashboard where you can upload CSVs, extract themes in ~30 sec per batch, review auto-drafted responses, and export results. Enough to demo to 3–5 early customers and validate demand. Cost to run: <$1/mo in API usage.
Known gotchas
- !Lovable doesn't scaffold survey/NPS collection—you'll upload CSVs manually or integrate an API to Typeform/Qualtrics for live ingest. DIY version 1 uses CSV uploads only.
- !Prompt-caching in Sonnet has a $0.90/M input token charge (90% discount vs. non-cached). Only worth it if you re-use the same system prompt >10 times/day (you will, after ~3 customers).
- !pgvector similarity search is fast but untuned clustering will group dissimilar themes together (e.g., 'API slow' and 'features slow' may cluster together). Use a fixed threshold (cosine distance >0.85) to cut false positives.
- !DeepSeek V4 Flash response drafts need 20–30% manual review—responses may be generic or miss context. For production, you'll want a hybrid (DeepSeek for volume, Sonnet for high-touch).
- !Supabase free tier has a 500MB database limit. At 500 feedback items × 5 customers × 6 months = 15K items (~3MB), you'll stay under. Upgrade to Pro ($25/mo) before hitting 10+ customers.
- !No per-client branding in Lovable MVP: all customers see the same UI. True white-label (custom logo, domain) requires a Next.js deploy + subdomain strategy (customer-name.yourplatform.com).
Compliance & risk reality check
A white-label CX platform touches customer feedback (often PII-laden), stores third-party API credentials, and may trigger automated responses to regulated contexts (healthcare, finance). Compliance scope varies by customer vertical, but three areas are non-negotiable: customer PII handling, data residency, and audit trails.
GDPR / CCPA for customer feedback (PII)
Customer feedback often contains names, email addresses, phone numbers, or account IDs. EU (GDPR) and California (CCPA) mandate that you have a Data Processing Agreement (DPA) with customers, data localisation if handling EU residents, and retention policies. You cannot store 'feedback from EU users' indefinitely—retention should match your stated policy (e.g., 'purge after 12 months' or 'purge on customer request').
Mitigation: Use Supabase's built-in GDPR tools (RLS, data residency in EU region for EU customers, automated purge policies). Document your DPA template; use Iubenda or Termly to generate GDPR-compliant Terms of Service. Mask PII (emails → [REDACTED]) before running LLM analysis.
HIPAA if healthcare clients
If any customer is a healthcare provider collecting patient feedback, feedback may contain protected health information (PHI). HIPAA requires a Business Associate Agreement (BAA), encryption at rest + in transit, audit logging, and access controls. Supabase can support HIPAA (encrypted storage, audit logs), but only in the 'Pro' tier with explicit HIPAA BAA signing.
Mitigation: For healthcare verticals, mandate Supabase Pro + sign HIPAA BAA. LLM analysis of PHI via Anthropic is acceptable if using Sonnet 4.6 with 'no retention' setting (Anthropic does not retain prompts when data-protection mode is enabled). Clearly document in your ToS: 'HIPAA support only for Pro customers; contact sales.'
CAN-SPAM / CASL for auto-generated responses
If your platform auto-sends responses to detractors via email, you're handling marketing emails. CAN-SPAM (US) and CASL (Canada) require an unsubscribe link, compliance with the "one-click unsubscribe" standard, and no false sender headers. AI-generated responses must still comply.
Mitigation: Route all auto-responses through Sendgrid (has CAN-SPAM compliance built-in). In your response template, always include a footer: 'You're receiving this because you submitted feedback. Manage preferences | Unsubscribe.' Test with Sendgrid's compliance checker before sending 1K+ responses.
SOC 2 Type II for enterprise sales
Large customers (100+ FTEs) will ask for SOC 2 Type II attestation. Supabase passes SOC 2 Type II as a vendor, but your application layer (access controls, audit logging, encryption keys) must also be auditable. Cheap DIY builds often miss audit trails and access controls.
Mitigation: Log all theme extractions (user, timestamp, customer_id, themes extracted) in an immutable audit table. Supabase's native audit logging can export to Datadog. For MVP: document your current security posture (TLS in transit, encrypted Supabase backups, IP whitelisting). SOC 2 audit costs ~$6K–$15K; delay until you have 5+ customers asking.
Build vs buy: the real math
10–16 weeks for a production-grade vertical-slice CX platform (NPS + closed-loop + theme-extraction only; not omnichannel feedback collection).
Custom build time
$13,000–$25,000 (RapidDev standard band). Bump to $25K–$35K if you need omnichannel feedback integration (Zendesk, Slack, Reddit mentions).
One-time investment
4–6 months (assuming 12–15 end-customer accounts at $99–$149/mo each = $12K–$22K/mo recurring revenue; LLM + infrastructure COGS ~$1.5K/mo = $20.5K/mo gross margin; at 10% net margin = $2K/mo profit; breakeven at $25K cost = 12.5 months, but revenue ramps month-over-month).
Breakeven vs buying
At 12 customers × $129/mo = $1,548/mo recurring, minus $800/mo LLM + infrastructure = $748/mo contribution. A $25K investment breaks even at month 33 (25 ÷ 0.748)—but only if you don't discount and churn is near zero. If you can cluster 5 customers pre-launch (committed to a 12-month contract), breakeven drops to month 6–8. The inflection point: once you reach 25+ customers, the marginal cost of adding one more is nearly zero (LLM cost scales sub-linearly at high volume due to caching), so the unit economics improve drastically—your net margin jumps from 10% to 40%+. Building today is betting that the Sprinklr / Qualtrics giants won't undercut you on SMB pricing; they haven't (their minimum SMB deal is still $1.5K+/mo), so the bet is reasonable.
Skip the DIY — RapidDev builds the production version
A Lovable MVP gets you a demo. Production needs auth that doesn't leak data, AI calls that don't bankrupt you, observability when models drift, and code you can audit. That's what we ship.
Discovery call (free)
30 minWe map your exact Digital Customer Experience (CX) Platform use case: who uses it, target volume, AI model choice, integrations, compliance scope. You get a detailed scope document and fixed-price quote within 48 hours.
AI-accelerated build
10–16 weeks for a production-grade vertical-slice CX platform (NPS + closed-loop + theme-extraction only; not omnichannel feedback collection).Our engineers use Claude Code, Lovable, and custom tooling to ship 3–5x faster than agencies. You see weekly progress in a staging environment — not a black box.
Launch + handoff
1 weekWe deploy to your infrastructure, transfer the GitHub repo, set up CI/CD and monitoring, and train your team. You own 100% of the source code, prompts, and model configurations.
What you get
Timeline
10–16 weeks for a production-grade vertical-slice CX platform (NPS + closed-loop + theme-extraction only; not omnichannel feedback collection).
Investment
$13,000–$25,000 (RapidDev standard band). Bump to $25K–$35K if you need omnichannel feedback integration (Zendesk, Slack, Reddit mentions).
vs SaaS
ROI in 4–6 months (assuming 12–15 end-customer accounts at $99–$149/mo each = $12K–$22K/mo recurring revenue; LLM + infrastructure COGS ~$1.5K/mo = $20.5K/mo gross margin; at 10% net margin = $2K/mo profit; breakeven at $25K cost = 12.5 months, but revenue ramps month-over-month).
30-min call. Fixed-price quote within 48 hours. No commitment.
Frequently asked questions
How much does it cost to build a white-label CX platform?
RapidDev's standard band is $13K–$25K for a vertical-slice build (NPS + closed-loop + theme extraction). If you want omnichannel feedback (integrating Zendesk, Slack, Reddit mentions), expect $25K–$35K and 14–20 weeks. DIY with Lovable is $25 + API credits (~$50–$100/mo in running cost); it takes 1 weekend but is not production-grade (no auth per-client, limited compliance). Buy-SaaS (Qualtrics, Sprinklr) costs $1.5K–$5K/mo but gives you an all-in-one platform and removes reseller margins.
How long does it take to ship a white-label CX platform?
RapidDev builds in 10–16 weeks (vertical-slice: NPS + closed-loop + theme extraction). A Lovable MVP (single-tenant, no auth per-client) runs 1 weekend. Production-grade (multi-tenant RLS, SOC 2 audit-ready, GDPR compliance) adds 4–6 weeks on top of RapidDev's build.
Can RapidDev build this for my company?
Yes. We've shipped 600+ applications including 80+ AI implementations in production. A white-label CX platform (NPS + closed-loop + theme-extraction) is a natural fit—3–4 month timeline, $13K–$25K investment. We recommend starting with a Lovable MVP to test market demand with 3–5 early customers, then transitioning to a RapidDev build once you have committed contracts. Free 30-min consultation: seopartner@rapidevelopers.com.
What's the difference between this and buying Qualtrics / Sprinklr?
Qualtrics ($1.5K–$5K/mo) is all-in-one: feedback, segmentation, journey mapping, reporting. But it's enterprise-focused and offers no white-label rebrand. This CX platform is a vertical slice (NPS + closed-loop + theme extraction only) designed for consultancies serving 5–20 mid-market SaaS clients at $99–$249/mo per customer. Reseller margin: 100% if you DIY on Lovable ($0.50 LLM COGS + $25/mo infrastructure = <$1/mo cost per customer), or 60–70% if you hire an agency to build ($25K build ÷ 20 customers = $1.25K per customer).
Does Sonnet 4.6 with prompt caching really cut costs by 90%?
Yes, but only if you re-use the same system prompt >10 times per day. Caching costs $0.90/M input tokens (vs. $3/M for non-cached). On a 1,000-item feedback batch (40K input tokens), the cached cost is $0.036 vs. $0.12 non-cached. After 3–5 customers, you'll hit that 10x/day threshold and the savings are real.
How accurate is the theme extraction?
Sonnet 4.6 achieves 85–90% accuracy on theme extraction (categories are correct; some edge cases may be mislabeled). DeepSeek V4 Flash is 70–75% (3–5 errors per 100 items). Accuracy depends on feedback quality—clear, grammatical feedback scores 95%+; typo-heavy, sarcastic feedback scores 65–70%. For high-stakes contexts (healthcare, fintech), manual review of 5–10% of themes is recommended.
Can I use this for multi-channel feedback (Zendesk, Slack, Twitter)?
The MVP handles NPS + open-text feedback (uploaded CSVs). Multi-channel integration (Zendesk API, Slack listener, Twitter stream) adds 4–6 weeks and $5K–$10K. For MVP, normalize feedback to a CSV schema and upload. For production, RapidDev builds connectors to your clients' existing tools (Zendesk, HubSpot, Slack).
What happens if Anthropic changes Sonnet pricing?
Your LLM cost is 80% of the total infrastructure cost (~$0.35 per customer per month in theme extraction). A 50% price increase in Sonnet would add ~$0.17/mo COGS per customer. At $149/mo retail, your margin drops from 65% to 63%—still healthy. If pricing doubles, you'd need to either increase prices by 10–15% or optimize to DeepSeek V4 Flash (which you can do in 2 weeks via prompt engineering).
Want the production version?
- Delivered in 10–16 weeks for a production-grade vertical-slice CX platform (NPS + closed-loop + theme-extraction only; not omnichannel feedback collection).
- You own 100% of the code
- AI cost monitoring built in
30-min call. No commitment.
