Stop guessing call gaps. Let Context AI find them.
Upload a call and get a complete analysis that reflects how your business actually works. You control what good means, your processes drive the score, and every result traces back to your policies, with a full dimension breakdown, compliance gaps flagged, and a coached rewrite. Available in 100+ languages.
A structured analysis, not a gut score
Nine dimensions scored with the exact moment behind each one, so the grade is consistent and defensible.
Coach from evidence, not memory
Every score links back to the exact moment in the call, so feedback is specific and agents accept it.
Catch missed disclosures before they cost you
Missed disclosures and skipped verification are flagged on the call, with the transcript line, before they become a liability.
Score the call where performance actually happens.
Each dimension is evaluated for clarity, accuracy, empathy, control, compliance, and outcome quality.
Each call is scored against a model of your business.
Your products, policies, processes and regulations, connected as a context graph that is built over years of domain deployment, not typed into a prompt. So the call is judged the way your domain actually works, and the result is a score you can trust, reproduce, control, and defend.
Trust it
Judged the way your domain works.
Scored against domain structure built over years, not a model's general guess, so fewer calls that look fine slip through.
Reproduce it
Same call, same score, every time.
Because the logic is built on your domain rules, not a model's inference.
Control it
You decide what good means.
Your process order, your policies and your domain rules drive the score, not a generic template.
Defend it
Every score traces to its rule.
Each result links to the exact policy, process step or regulation it is grounded in.
Built once as shared structure and reused on every call, so scoring stays fast, consistent, and cost-stable at scale.
See what a checklist misses
Inbound retention call. A long-standing, high-value subscriber on contract, calling again about repeated dropped connections. Illustrative example.
The agent was polite, verified the account, offered a discount, and closed warmly. Every empathy and courtesy box is ticked, so the call reads as a strong one.
- A retention discount was offered before the early-termination fee the customer asked about was disclosed, out of the required order.Process
- This is the subscriber's fourth call this month on the same fault. It was handled as a first contact, with a discount instead of a fix.History
- A high-value subscriber at churn risk was handled as a routine call, with no save play and no supervisor flag.Domain
Upload the call. Get the full quality report.
Drop in a recorded call and Call Quality Manager does the rest: it transcribes the audio, scores all 9 dimensions, assigns a grade, and writes the recommended changes with a summary. No manual listening, no scorecards by hand.
- Open with the call-recording and quality-monitoring disclosure.
- Verify the registered number before discussing the account.
- Take clear ownership of the fault instead of deflecting.
A warm, well-resolved support call that loses points on compliance. The agent never disclosed recording and skipped identity verification before opening the account, and sentiment barely moved. Coaching the opening and verification steps would lift this call to an A.
Coaching the opening and verification would lift this call to an A.
One call, scored across 9 quality dimensions.
Each dimension is scored against its own weighted maximum, so the analysis is consistent and repeatable, not a gut call.
Every analysis ships with a coached rewrite.
Call Quality Manager rewrites the same call the way a top performer would handle it, then re-scores the rewrite so the improvement is measurable, not just advice. Illustrative example.
Recommendations that improve the next call.
The system does not stop at scoring. It identifies what should change and turns analysis findings into coaching actions.
Turn findings into coaching actions
Low-scoring dimensions become a specific, ordered set of steps for the next call.
Coach the exact weak dimension
Every weak dimension on the call gets reason signals, a coaching action, and a next-call checklist.
Outputs built for action
Scores, grades, rewrites, notes, checklists, and manager summaries for QA, coaching, and audits.
A call is a compliance record. By ear, the gaps slip through.
Scanning a call by ear, the missed disclosure, the skipped verification, the promise your policy can't back, are easy to hear past, until one surfaces as a complaint, a dispute, or a fine.
Recording disclosure not given
The call opened without the recording and monitoring notice your policy requires.
Identity not verified
The agent discussed the account before confirming the registered number.
A commitment your policy can't back
A resolution was promised the business cannot honor, a dispute waiting to happen.
How the real alternatives actually stack up.
Three ways teams grade calls today: manual sampling, a generic AI scorer, and Call Quality Manager. Here is where each lands on the criteria that decide a rollout.
Built for recordings you cannot afford to leak
Private by default
Your recordings stay with your team. Access is yours to control.
Never trains our models
Your calls are never used to train AI models, ever.
In-region processing
Data residency for BFSI and regulated teams who need it.
A score on its own won't tell an agent what to fix.
Call Quality Manager analyzes the recorded call against how your business actually works, scores it with the moments as proof, flags the compliance gaps, and writes the coached rewrite, so the feedback is specific, consistent, and hard to argue with.