Price: $2.99
(as of Oct 25, 2024 06:07:51 UTC – Details)
A Clairvoyant. An Empath.
Lives in danger, and a ticking clock.
Just another day at the office.
Agent Alex Kane uses her visions of the future to save lives in her job at the Grey Raven Paranormal Agency. Emotion is a weakness she can’t afford.
In order to stop her latest horrific vision from coming true, she has to team up with a new partner – an Empath. He can see straight through Alex’s icy exterior to the intense, broken person beneath. The nature of his talent makes people – Alex especially – uncomfortable around him, and he’s had to push people away in order to do his job.
They are thrown together on a mission to prevent a catastrophic event. But Alex’s visions of their future together – a future she wants to prevent at all costs – make it hard to maintain professional distance.
Together, they must navigate political intrigue, danger, and their own complicated relationship to avert an international disaster before time runs out.
Fans of Ilona Andrews’s Hidden Legacy series and Annette Marie’s Guild Codex will love this fast-paced enemies-to-lovers Urban Fantasy Romance you won’t want to put down!
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Shattered is the first book in Closer to the Sun, a new series that combines Romance, Urban Fantasy, and Suspense. It follows the lives of ordinary people with extraordinary talents as they navigate a world that is – and is not – exactly like our own. The closer you fly to the sun, the farther you have to fall.
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Read the beginning at http://ivytowerbooks.com/shattered
ASIN : B0CGXJWSHM
Publisher : Ivy Tower Books, LLC (September 19, 2023)
Publication date : September 19, 2023
Language : English
File size : 1234 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Enabled
Print length : 232 pages
Customers say
Customers find the story amazing, compelling, and fun. They appreciate the interesting characters and the fast-paced read. Readers also mention the book is a fast-paced read with banter.
AI-generated from the text of customer reviews
