Solutions

What are you trying to get done?

Practical guides to the work people hand to AI, by task and by industry. Read the real approach. When you want it run end to end, Physea's MCP does that.

By task

AI for overdue invoices & payment follow-ups AI can draft and send payment reminders in the right tone, time them to a sensible cadence, pull the exact amount and invoice number from your records, and retry failed card charges. The hard part is not the writing; it is matching each message to the right account, the right contractual hook, and the right moment, then doing it consistently across every late payer without nagging the ones who already paid.
Drafting customer emails, replies & follow-ups with AI Use AI to read each message's intent first, then draft a reply that matches the customer's tone and pulls in the real details: their order number, appointment time, or the exact line they wrote. The hard part is not the writing, it's the judgment about intent, tone, timing, and grounding. This page covers replies, support-inbox tagging, lead follow-ups, and short SMS reminders and confirmations.
Summarizing documents, meetings & transcripts with AI Transcribe or extract the text, then ask a language model for the specific output you need: decisions and owners, flagged clauses, recurring themes, or study notes. The hard part isn't shrinking the text; it's keeping what matters, attributing it correctly, and turning it into something you act on. A generic summary is easy and usually useless. A summary that captures the one clause that changes the deal is the actual job.
Extracting data from documents, receipts & forms with AI Use OCR to turn the image into text, then a language model to pull named fields into a structured record. The hard part isn't reading the words; it's handling messy layouts, validating numbers, and routing the result into the system that needs it. Done by hand it's slow and error-prone. Modern AI gets you to roughly 90% on clean documents, and the last 10% is the work.
Forecasting demand, staffing & inventory with AI AI forecasts demand by learning the patterns in your own history (sales, bookings, weather, seasonality) and turning that prediction into a concrete plan: who to schedule, how much to reorder, which appointments will no-show, which jobs will run over. The forecast is the easy part. The hard part is turning a number into a roster, a purchase order, or a rebooking offer that respects your real constraints.
Pricing, quotes & competitor analysis with AI AI helps with pricing in two ways: it reads the inputs that should set a price (competitor rates, demand, part specs, material costs, lead times) and it turns those inputs into a number you can actually send, a quote, a rate, a discount, a route price. The reading is the easy half. The hard half is the judgment, what's a fair comparison, how much margin to defend, when to move, and getting the number into the tool where the deal lives.
Responding to & learning from online reviews with AI AI helps two ways: it drafts replies to Google, Yelp, Airbnb, Vrbo, and Yotpo reviews that name the specific complaint, take responsibility without excuses, and stay inside each platform's rules; and it pulls weeks of reviews together to rank the top recurring complaints so you fix the actual cause, not just answer the symptom. The drafting is the easy half. The value is in turning the patterns into operational changes.
Turning business data into reports with AI AI can pull your sales, ad, and KPI numbers from the tools they live in, do the comparisons you'd do by hand, and write up what changed. The hard part isn't the math; it's asking the right question of the data, comparing like with like, and not mistaking a small or noisy number for a trend. Done well, you get a report that says what to do, not just a table of figures.
AI for bookkeeping, reconciliation & sales tax AI can match your POS sales to bank deposits, calculate tax across states, and flag where purchased goods don't match what arrived, by reading the same records you would and doing the cross-checking faster. The judgment still matters: deposits come in net of fees, tax rules differ by state, and a short shipment isn't always an error. The honest answer is that the work is mostly tedious matching, not hard math.
Generating marketing copy, product descriptions & ads with AI Feed the model your real inputs (supplier specs, brand voice, the offer, the audience) and ask for several distinct angles, not one polished paragraph. The quality lives in the brief and the constraints, not the prompt's cleverness. AI handles the bulk of product descriptions, ad variations, and social posts; a human still owns the claims, the facts, and the final cut.

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