Solutions
Production-grade solutions that turn our open-source packages into deployable AI systems for specific business problems. Pick one, follow the DIY tutorial to see how it's done, download the examples and deploy them on your own infrastructure — for free — or tell us which ones you want customized and deployed.
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32 solutions · page 1 of 3
agnostic-plan-takeoff-to-rfp-agent
A general contractor's estimator spends 2-3 days manually measuring plans, counting fixtures, and typing up scopes for each trade. Mistakes in takeoff lead to under-bid jobs or angry subs. The process is tedious, error-prone, and scales poorly with project volume.Convert plan sets and spec docs into a bill of materials and RFP drafts in minutes, not days.
agnostic-review-response-agent-4
The owner or general manager of a 1-5 location independent restaurant spends hours each week manually crafting responses to Yelp, Google, and TripAdvisor reviews. Responses are often delayed, inconsistent in tone, or skipped entirely, damaging the restaurant's online reputation. With thin margins and a lean team, there's no budget for a dedicated marketing person. The GM needs a way to automatically generate appropriate, on-brand replies that maintain a positive presence without adding to their administrative burden.Never miss a Yelp or Google review again with consistent, on-brand replies.
cohere-document-pipeline-for-bigcommerce-smb-order-processing
Small e-commerce merchants on BigCommerce waste hours manually transcribing orders from emailed PDFs and scan attachments into the platform, leading to data entry errors and delayed fulfillment.Automatically scan and process emailed purchase orders and quote requests into BigCommerce, cutting order entry time from minutes to seconds.
agnostic-recruiter-resume-scoring-agent-2
A solo recruiter at a 5-person firm spends 6+ hours per role manually scoring 50-200 resumes against a rubric. Inconsistent scoring leads to missed top candidates and client complaints. Enterprise ATS scoring tools are too expensive and complex. The recruiter needs a fast, fair, and auditable way to rank candidates without hiring more staff.Score 200 resumes per role in seconds with a consistent rubric, no spreadsheets.
agnostic-no-show-chase-agent
The studio manager spends 30 minutes every morning texting clients who no-showed or late-canceled yesterday. They have to manually check the booking system, compose a message, and decide whether to charge a fee or offer a makeup class. This inconsistent enforcement frustrates regulars and fails to recoup lost revenue. Without automation, the studio bleeds class capacity and staff morale drops.Automate late-cancel and no-show follow-ups with personalized reschedule offers and penalty enforcement.
agnostic-receipt-classifier-agent
A bookkeeper at a 3-person CPA firm spends 10+ hours per week manually sorting client receipts forwarded via email or upload. Each receipt must be reviewed to identify the vendor, extract the amount, and assign the correct GL category. During tax season, this backlog balloons, causing overtime and errors. The bookkeeper needs a way to automate this drudgery so they can focus on reconciliations and client advisory.Eliminate manual receipt categorization with an AI agent that extracts vendor, amount, and GL category from client uploads.
agnostic-listing-copy-multiplier-2
As a listing agent, you spend hours rewriting the same property description for MLS, Zillow, social media, and printed brochures. Each platform has different character limits, tone requirements, and SEO keywords. You often miss updates across channels, leading to inconsistent messaging and lost showings. This manual copy-paste grind eats into prospecting time and frustrates your team.Generate MLS, Zillow, social, and brochure copy from one draft in seconds.
agnostic-return-reason-agent-2
A Shopify store owner receives dozens of return requests daily, each requiring manual review to determine if the item is defective, wrong size, or buyer's remorse. The owner must then decide whether to refund, replace, or offer store credit, consuming hours of time that could be spent on growth. This manual process is error-prone and inconsistent, leading to customer frustration and lost margin.Automatically classify return reasons and trigger refund/replace decisions without human review.
agnostic-prior-auth-agent
A dental or optometry clinic's billing specialist spends up to 25 minutes per prior-authorization request, manually filling payer-specific forms. Each payer requires different fields, and errors cause rework and delays. With 10-20 requests per day, this consumes 4-8 hours of staff time, delaying care and increasing administrative costs. The specialist needs a tool that auto-fills forms from the EHR and submits them via payer portals.Cut prior-auth processing from 25 minutes to under 2 minutes per request.
agnostic-per-tenant-llm-cost-chargeback-2
As a product manager at a vertical SaaS company, you need to offer AI features to your SMB customers but each customer may use different LLM providers based on their plan. You lack per-tenant cost tracking, making it impossible to charge back usage accurately. This leads to margin erosion and prevents you from scaling AI features profitably. You need a solution that captures LLM costs per tenant and integrates with your existing billing system.Track and bill each SMB customer for their AI usage with granular cost attribution.
agnostic-referral-letter-drafter-2
Veterinary practice managers and associate vets spend 15+ minutes per referral case manually summarizing medical history, lab results, and treatment plans into a letter for specialists. This paperwork eats into appointment time and leads to delayed referrals, frustrated specialists, and lost revenue. The process is error-prone, with vets often omitting critical details due to time pressure. An AI agent that reads the medical record, extracts relevant data, and drafts a formatted letter can cut drafting time by 90% and improve referral quality.Draft specialist referral letters in under 2 minutes by extracting key findings from PIMS records.
openai-quote-assistant
When a customer calls asking 'How much to fix my brake noise?', the service advisor has to drop everything, walk to the bay, and interrupt a mechanic. That kills bay productivity and makes the customer wait on hold. Worse, the advisor often lacks the part-pricing data at their fingertips, leading to rough ballpark quotes that later get disputed. The shop owner sees advisor burnout and lost revenue from calls that never converted.Convert inbound 'how much to fix X' calls into structured estimates without tying up your service advisor.