Score every sales call on the words, the delivery, and the visuals, against your own methodology. Then turn each one into the next action.
TYLER BRYDEN · CO-FOUNDER & CEO · DANIEL KHARLAS · SPEAK AI
speakai.co1 / 10
Who we are
We have transcribed a very large number of conversations.
Since 2018, across sales calls, interviews, focus groups, and meetings, in 100+ languages. Along the way we pulled everything a transcript can give: topics, keywords, entities, sentiment, summaries, action items, custom fields, whole dashboards built on the words.
And then we hit the ceiling. The words stopped explaining the outcome. To go further we had to analyze the layer underneath them.
Speak AI2 / 10
The layer underneath
People say one thing and show another.
"Yeah, that makes sense" while the face says the opposite. We miss it live because we are busy communicating: thinking about the next question, watching the clock, running the demo. The transcript records the agreement and loses the hesitation entirely.
What the transcript recorded
"Yeah, no, that makes sense."
Logged as agreement. Summarized as alignment. Nothing in the words says otherwise, so nothing downstream does either.
The audio heard the pause before it. The video saw this. Neither one is in the transcript.
Speak AI3 / 10
What that unlocks
This is what makes sales scoring real.
Layer 1
The words
What the rep said
Objections raised and handled
Next steps captured
Layer 2 · + Audio
The delivery
Tone, energy, and pace
Confidence and hesitation
Talk ratio and interruptions
Layer 3 · + Video
The visuals
What was on screen, and when
The reaction that contradicted the words
The moment tied to the visual
Scored on your methodology, not a generic model of selling.
01Ask in AI ChatOpen one call, ask a question. No setup, no config, an answer grounded in the words, the delivery, and the visuals.Open a call
02Automate the outputRun that prompt on every new recording automatically. Summaries and scorecards land the moment the call ends.Automations
03Write into fieldsAnswers stop being paragraphs and become structured data: delivery score, objection, why it stalled, next action.Fields
04Quantify it in dashboardsThose fields roll up across the team: scores by rep, by call type, by stage, trending over time.Dashboard
05Drive it programmaticallyA developer key and the MCP server put every one of these operations under your own code.MCP
06Use it from your own surfacesThe same MCP works from Claude, ChatGPT, the CLI, and your internal tools.MCP docs
07Encode your evaluation frameworkFeed in your rubric and your best coaching samples, and have the MCP generate and refine the scoring prompts for you.Build it
08Sync with your CRMTwo-way: deal data gives the analysis context, and the scores flow back onto the record so outcomes correlate to behavior.Integrations
Speak AI6 / 10
Who it is for
Same engine, three jobs.
Individual rep
Coach yourself
Score your own calls before your manager does
See where the delivery dropped
Get the next action written for you
Manager
Coach the team
Every call scored, not just the ones you had time for
Trends per rep, flags on the calls worth your time
A dental sales training organization runs Speak AI across its whole coaching practice: 20,651 recordings captured and 20,415 analyzed, roughly 6,500 hours of conversation, with automations scoring calls the moment they land.
Verified live in the platform 2026-08-24
Reviewing that volume by hand was never possible. Scored automatically instead, it represents 50,000+ hours of manual review avoided and $900K+ saved.
Published case-study methodology
Presenter note: confirm the updated savings figures before this slide. Live counts above are verified; the hours/dollars line reuses the existing published claim.
Speak AI9 / 10
For everyone here today
We turn it on and set it up with you.
A dedicated 1-on-1 session: we enable multimodal analysis on your workspace, set it up on your own calls with your own scoring criteria, and include credits to run it. Bring one of your calls and leave with it scored and actioned.
