ElevenLabs Develops Efficient Voice Agent for Document Support

ElevenLabs
has
introduced
a
voice
agent
designed
to
efficiently
handle
user
inquiries
related
to
its
documentation,
achieving
a
resolution
rate
of
over
80%,
according
to

ElevenLabs.
The
voice
agent
processes
approximately
200
calls
daily,
demonstrating
significant
success
in
addressing
user
queries.

Performance
and
Evaluation

The
voice
agent,
powered
by
a
large
language
model
(LLM),
has
been
evaluated
for
its
ability
to
solve
or
redirect
inquiries
effectively.
Human
validation
of
150
conversations
revealed
an
81%
agreement
rate
between
the
LLM
and
human
evaluators
on
successfully
resolved
inquiries.
The
agent
also
demonstrated
an
83%
agreement
on
maintaining
adherence
to
the
knowledge
base.

Furthermore,
89%
of
relevant
support
questions
were
either
answered
or
correctly
redirected
by
the
documentation
agent,
showcasing
its
capability
in
managing
straightforward
queries.

Strengths
and
Limitations

Strengths

The
LLM-powered
agent
excels
in
resolving
specific
questions
that
align
well
with
the
available
documentation.
It
effectively
guides
users
to
relevant
pages
and
provides
initial
guidance
on
complex
queries,
proving
beneficial
for
questions
such
as
API
endpoints,
language
support,
and
integration
queries.

To
optimize
its
performance,
ElevenLabs
recommends
targeting
users
with
clear
questions
and
utilizing
redirects
for
more
complex
inquiries,
enhancing
the
efficiency
of
the
support
process.

Limitations

Despite
its
strengths,
the
agent
encounters
challenges
with
vague
or
account-related
inquiries
that
require
deeper
investigation.
The
voice
medium
is
less
suited
for
sharing
code
or
handling
complex
technical
issues,
prompting
ElevenLabs
to
suggest
redirecting
users
to
documentation
or
support
channels
for
such
queries.

Development
and
Configuration

The
voice
agent
is
configured
with
a
system
prompt
that
guides
its
responses,
ensuring
it
remains
focused
on
ElevenLabs
products.
A
comprehensive
knowledge
base,
including
a
summarized
version
of
all
documentation,
supports
the
LLM
in
providing
accurate
answers.

Three
primary
tools
are
integrated
into
the
agent’s
functionality:
redirecting
to
external
URLs,
email
support,
and
documentation,
offering
versatile
pathways
for
user
inquiries.
The
agent’s
evaluation
tooling
assesses
conversations
against
predefined
criteria,
ensuring
ongoing
improvement
and
reliability.

Continuous
Improvement

ElevenLabs
recognizes
the
limitations
of
LLMs
in
solving
all
types
of
queries,
particularly
in
a
rapidly
evolving
startup
environment.
However,
the
company
emphasizes
the
benefits
of
automation,
allowing
its
team
to
focus
on
complex
challenges
as
the
community
expands
the
potential
of
AI
audio
technology.

The
agent,
powered
by
ElevenLabs
Conversational
AI,
serves
as
an
effective
tool
for
navigating
product
and
support
questions,
continuously
refined
through
automated
and
manual
monitoring,
reflecting
the
company’s
commitment
to
enhancing
user
support
experiences.

Image
source:
Shutterstock