94%
Transcription accuracy
28
Conversational signals
40+
Languages supported
<2s
Analysis latency
Architecture
How it works.
Ingest & transcribe
Calls are ingested via API, CRM integration, or direct upload. A speaker-diarised transcript is produced using our fine-tuned acoustic model — separating agent, prospect, and background noise with 94% word-error-rate accuracy across 40+ languages.
Multimodal analysis
Each transcript is processed through a dual-pathway architecture: a prosodic pipeline extracts pitch trajectory, speech tempo, and energy variance; a semantic pipeline applies transformer-based sentiment modelling and latent-topic extraction across 28 distinct conversational signal classes.
Surface & act
Structured output is delivered to your CRM, coaching dashboard, or webhook — timestamped signal events, deal-risk scores, objection clusters, and auto-generated call summaries with recommended next actions.
Interactive demo
Watch it analyse a call.
pipeline
Ready to analyse
Results appear here once the pipeline finishes
Sample output
What the analysis returns.
Key moments
Timestamped events — objections, price discussions, buying signals, and pivot moments — flagged automatically.
00:29 — Implementation timeline objection raised (8 vs 12 weeks)
01:20 — Cost objection neutralised: extra weeks within project price
02:27 — €1,200 → €1,080 annual pricing discussed
02:53 — Follow-up call booked: Thursday 14:00
Diarised transcript
Speaker-separated, timestamped, with per-utterance emotion and sentiment labels.
Good afternoon — Thomas from Arcum. How can I help you?
Hi Thomas. I'm calling about the proposal. We have a few questions.
Of course, great to hear from you. What are your questions?
The implementation timeline — you mention eight weeks, but our IT says twelve.
Eight weeks is our standard for clean-room. With legacy integrations we plan for twelve — no extra cost.
Coaching output
Per-rep feedback from signal patterns — what worked, what to improve, what to replicate.
low — deal is progressing
✅ Objections handled quickly and factually
⚠️ Ask who the decision-maker is earlier in the call
⚠️ Rep talk ratio 54% — target ≤ 45%
Capabilities
What’s under the hood.
Prosodic feature extraction
Acoustic analysis of pitch, tempo, and energy patterns — detecting hesitation, confidence shifts, and rapport dynamics that text alone cannot capture.
Sentiment trajectory modelling
Transformer-based sentiment scored at sentence-level resolution, mapped over the full call arc to identify pivot moments and emotional inflection points.
Real-time signal detection
Live mode surfaces 28 conversational signals — buying intent, competitor mentions, objection patterns, pricing sensitivity — with sub-2-second latency.
Multilingual diarisation
Speaker separation and language identification across 40+ languages in a single call. Code-switching handled natively within the same transcript.
Compliance & redaction
Automatic PII detection and redaction, configurable retention policies, and full audit trails. SOC 2 Type II certified, GDPR and HIPAA ready.
CRM-native integration
Bi-directional sync with Salesforce, HubSpot, and Pipedrive. Call scores, summaries, and signal events written back to the contact record automatically.
Use cases
Built for revenue teams.
Sales teams
Identify calls with high deal-risk before they go cold
Auto-score each rep against your ideal call framework
Surface the exact objections blocking pipeline progression
Generate battle-card gaps from competitor mention clusters
Customer support
Detect escalation signals before the customer asks for a manager
Measure CSAT-predictive acoustic markers at scale
Cluster recurring issue topics across thousands of calls per day
Reduce manual QA from hours to minutes per team
Revenue operations
Correlate call behaviour patterns with closed-won outcomes
Build rep ramp models from first-call signal distributions
Enrich CRM records with structured, machine-readable call data
Benchmark conversation quality across regions and segments
Product team
Talk directly to the
product manager.
Have questions about integrations, custom use cases, or how CallIQ fits your team's workflow? Mo oversees AI Call Analyser and is happy to talk specifics.
Mo
Head of Innovation & Engineering · Business Strategy · PM
Mohosoft