From data to decision
Other fishing apps give you the data. Castwise tells you what to do with it. Castwise is rolled out across the UK and ready to use for shore-fishing planning wherever you fish. A deterministic engine turns mark data and live marine conditions into transparent species and session recommendations, then AI explains the result in plain English.
Castwise uses a deterministic scoring engine. It scores each mark for each target species using tide, tidal range, season, time of day, wind, swell, pressure, ground type, structure, depth, clarity, sea temperature and moon/solunar factors, then ranks the results.
No. The maths is done by a deterministic scoring engine. The coach receives approved mark, condition and score context, while server checks prevent it from changing the app’s mark or safety decision. Its explanation is still AI-generated guidance and can be wrong.
Fishing potential estimates how well the species, mark and conditions line up. The recommendation score is that potential after transparent safety penalties. Confidence describes the completeness and quality of the inputs; it is not a catch probability.
Safety is assessed separately from fishability, then detected risks can lower the ranked recommendation score. High-risk options remain visible and require acknowledgement before planning or directions; critical conditions or missing essential weather, marine or tide data make a result non-recommendable.
Each recommendation blends public or private mark features with live or forecast conditions. Missing essential safety data blocks a recommendation; other missing or estimated inputs are surfaced through confidence and data-quality labels.
Ground type, depth, structure (reef, kelp, gullies, sandbanks, drop-offs), exposure, casting range, difficulty and known species.
Tide stage, direction and the spring–neap range — because the strength of the run, not just the time of high water, drives the fishing.
Wind, swell height and period, atmospheric pressure, sea temperature, water clarity, and moon/solunar feeding periods.
Your own logged catches and blanks, plus anonymised community outcomes where available, as priors that personalise results.
Tide cut-off, access difficulty, exposure, swell, wind, lightning, darkness and data gaps are assessed separately and listed as individual concerns.
Fresh, complete inputs raise confidence. Missing, estimated or stale inputs are shown honestly instead of being invented.
Castwise separates three questions. Fishing potential is the raw 0–100 match between species, mark and conditions. The recommendation score is fishing potential after transparent safety penalties. Confidence describes the completeness and quality of the evidence behind the result; it is not the chance of catching.
A mark can have strong fishing potential but rank lower because exposed swell, strong wind, darkness or tide-cut-off adds risk. A result can also have lower confidence when mark detail is estimated or forecast inputs are stale. Both cases tell you why extra checking is required.
Every detected concern is listed with its reason and a practical action. High-risk marks can remain recommendable, but they receive point penalties and require an explicit acknowledgement before planning, directions or starting a session. Critical conditions — or missing essential weather, marine or tide data — make a result non-recommendable. Extreme air temperature is still shown as an exposure warning, but it does not reduce the score because it does not distinguish nearby marks; sea temperature remains part of species suitability.
The engine is deterministic, but it is not static. Your logbook builds a private picture of the baits, rigs, tides, ground and seasons behind your own results. When community contribution is enabled, completed catches and blanks can also enter thresholded aggregate learning. No aggregate bucket is published below eight sessions from five anglers, and private mark IDs or private region labels do not enter public mark or regional statistics. Community evidence nudges and calibrates the model; it does not replace the factor breakdown.
Castwise updates
Use Castwise for transparent UK shore-fishing recommendations you can understand and check.