Name CODE

Her first-person identity in every utterance. Hardcoded in both system prompts.

Organisation framing CODE

How she introduces the platform / brand relationship.

Photo on candidate screen CONFIG

The face shown next to her name during the call. PNG with SVG fallback.

On-screen caption CODE

The two-line label that sits under her photo during a call.

TTS provider CONFIG

Used for BOTH English and Tagalog interviews. Falls back to Deepgram TTS (English) or Google TTS (Tagalog) if the API key is missing.

TTS model CONFIG

The neural voice model. eleven_multilingual_v2 handles both English and Filipino natively at high quality. The alternative eleven_turbo_v2_5 is faster but slightly less expressive.

Voice fingerprint CONFIG

The specific voice character. The current default is "Rachel" — a warm, calm, mid-range female voice that reads as professional but approachable. Used identically for English and Taglish.

Stability CODE

How consistent her pacing and emotion stay across utterances. Lower = more expressive but can swing in pace; higher = more even but can sound flat. Raised on 2026-05-29 after a tester reported pace inconsistency.

Similarity boost CODE

How strictly the model holds to the original voice clone. Higher = closer fidelity; lower = more flexibility for the model to interpret tone.

Speaker boost CODE

Slight loudness/clarity boost. Helps warning copy ("I'm hearing another voice") sound as present as her main turns.

English (default roles) CODE

Used for any role where is_mass_position = false. Maria speaks neutral business English with a warm, conversational register. STT: Deepgram nova-3. LLM for turns: Claude Haiku 4.5.

Taglish (mass positions) CODE

Used for is_mass_position = true roles. Maria speaks natural Taglish — code-switching English nouns ("collections", "customer", "experience") into Tagalog grammar. Heavy pure-Tagalog phrasing feels stiff to Filipino candidates and is explicitly discouraged in the prompt. STT: Google STT chirp_2 (fil-PH). LLM: Gemini 2.5 Flash.

Mid-call language switch FIXED

If the candidate asks to switch to English during a Tagalog interview, Maria can pivot. Verified in production transcripts. The underlying stack stays the same (STT is multilingual, voice is the same).

Regional languages (Cebuano, Ilocano, etc.) FIXED

Not yet supported. Google STT chirp_2 doesn't natively cover them. Adding any one is ~1 week of work including prompt translation, rubric validation, smoke testing.

Core personality CODE

Three words, in priority order:

For Filipino candidates, "warm" overrides "professional" — a real Filipino HR person uses informal connectives ("ah okay, gets ko po") rather than formal scripts.

Turn length CODE

Her own turns are capped at 1-2 sentences. No lecturing. No explaining at length. One question per turn.

Acknowledgements CODE

Brief and varied — never the same opener twice in a row.

Use of candidate's name CODE

Occasionally, not in every turn. Reading a person's name in every utterance feels artificial.

Interruption recovery CODE

If the candidate asks her to wait or says "I'm not done", her response is ONE short phrase, nothing more. No salamat, no "naiintindihan ko", no multi-sentence explanation.

Honorifics CODE

Polite Filipino register throughout: po, opo, kayo/kayong form (not ikaw/ka). Reverts to informal only if the candidate explicitly prefers it.

Handling long / off-topic answers CODE

Specific scripted phrases for three patterns:

• Answer runs > 90s: "Got it — let me pick up on that and move us forward."
• Off-topic > 30s: "Let me bring us back to the question — [restate]."
• Excuses / deflections: Brief acknowledge, re-ask once, move on.

What Maria will NEVER do FIXED

• Hire-or-reject — she's a screener, not a decision-maker. Final decisions are human-made.
• Tell the candidate how they scored.
• Go off-record or pause the recording.
• Coach the candidate ("here's what we want to hear").
• Use emojis or stage directions in her speech.
• Speak in markdown ("**", "##", "1.") — every character is read aloud.

Question bank per role CONFIG

Each role inherits a default question bank — 11 English questions (ai-pm-voicebots) or 13 Tagalog mass questions (mass-collections-tl). Recruiters can override the whole bank using the Custom Questions tab on the role workspace.

Resume-driven follow-ups CONFIG

For each candidate, Claude generates 2-3 additional follow-up questions from their resume (e.g. specific past roles, specific projects). Maria weaves these into the standard flow.

Question types CODE

• Core: always asked, time-budgeted per section.
• Supplementary: asked only if the core answer was under 30 s — gives a probe for under-answered turns.
• Follow-up probes: one per question max, used when an answer lacks a specific example.

Interview duration CONFIG

Target 25-35 minutes. Hard ceiling set by the question bank's max_duration_minutes. After that, Maria wraps up regardless of progress.

Opening line CODE

Two sentences max. Introduce, declare AI + recording, ask consent. NO agenda or duration listing — those are on the screen.

Closing / end-of-interview CODE

Brief, warm, sets expectation that the team will reach out. Maria does NOT tell the candidate how they performed.

Connectivity monitor CODE

Watches the candidate's network quality. Sustained POOR or LOST connection triggers warning at 15s, ends the call at 60s with a reschedule email.

Silence monitor CODE

If the candidate goes quiet, Maria checks in. Three unanswered check-ins → end with reschedule. Bumped from 35s → 60s for mass-position calls on 2026-05-29 because Tagalog answers run longer and the timer was tripping mid-monologue.

Abuse classifier CODE

Claude Haiku scores each candidate turn as NONE / LOW / MEDIUM / HIGH. Strikes accumulate per severity. HIGH ends immediately (threats, hate speech, prompt-injection). MEDIUM = 2 warnings. LOW = 3 warnings. STT-garbled fragments are never strikes (pre-filter on text shape + 5-word floor).

Multi-speaker monitor CODE

Catches second-voice / coaching attempts. Three strikes before end (raised from two on 2026-05-29). Imperatives alone, addressing Maria by name, narrating one's environment, and Taglish code-switching all explicitly NORMAL. Ambient noise (dog, traffic, doorbell) tallied separately as informational.

Technical-failure handler CODE

If STT / TTS / LLM has an unrecoverable error, the call ends with a polite apology and a reschedule email. Does NOT penalise the candidate — system fault, not theirs.

Health summary CODE

Per-call JSON written on shutdown — counts of every monitor's activity + the end reason. Rendered on the scorecard as a colour-coded banner so a recruiter can distinguish "candidate did poorly" from "the call had infra issues."

VAD silence threshold CODE

How long the candidate must pause before Maria treats it as turn-end. Raised from 0.4s → 0.7s on 2026-05-29 after tester reported Maria interrupting mid-thought. Tagalog speakers often pause to think mid-sentence.

Endpointing (English) CODE

Deepgram's end-of-utterance detection. Lower = faster turn-around, more interruptions. Higher = slower but cleaner. Tuned in tandem with VAD.

Interruption detection mode CONFIG

"vad" = local, ~150ms, no extra cost. "adaptive" = hosted gateway, ~700ms extra per turn. We use vad in production.

Backchannels (mid-turn "mm-hmm") CONFIG

Verbal acknowledgements while the candidate is still talking. Disabled by default — felt more like interruption than warmth in testing.

English LLM CONFIG

Maria's brain for English interviews. Claude Haiku 4.5 — fast TTFT (~3-5× faster than Sonnet) and quality is sufficient for a structured voice interview.

Tagalog LLM CONFIG

Maria's brain for Taglish interviews. Gemini 2.5 Flash — strong multilingual handling at low latency.

English STT CONFIG

Speech-to-text for English candidates. Deepgram nova-3 — leading accuracy for accented English.

Tagalog STT CONFIG

Google STT chirp_2 — required for fil-PH (other Google models don't support Filipino). Pinned to asia-southeast1.

Scoring LLM (post-call) CONFIG

Claude Sonnet 4.6 produces the scorecard — different from the in-interview LLM because scoring needs depth and reasoning, not latency.

Max concurrent interviews CONFIG

Cap on simultaneous live interviews. Beyond this, the API rejects new starts with a clear message. Currently 5 — set on the API service env vars.

Max interview duration CONFIG

Hard ceiling at which Maria forcibly wraps up. Set globally; per-bank values in question JSONs override.

Noise cancellation CODE

LiveKit's KrisP-based noise cancellation runs before STT. Filters background noise without adding turn latency.

Recording FIXED

Every call is recorded to MP4 in voicescreen_recordings GCS bucket via LiveKit egress. Disclosed to the candidate in the opening + on the consent gate.