Overview · Resources
Buy software and AI with your eyes open.
Guides, calculators and checklists we wish every client had before their first vendor call. No gated PDFs, no email wall — just the things that help you make better decisions, whoever you hire.
AI: build it right
GuideWhat AI development really costsWhat drives AI project cost — the model is the cheap part. Effort by phase, hidden costs vendors skip, running costs and how to budget safely.GuideWhy AI pilots die before productionAI pilots stall on data, unclear value, cost and trust — rarely on the model. Seven failure patterns and the fixes that get AI into daily use.GuideRAG vs fine-tuning vs promptingRAG adds knowledge, fine-tuning changes behaviour, prompting is where you start. How to choose — with a decision tree, costs and pitfalls.Guide9 tricks that make AI demos lieCherry-picked questions, clean sample data, hidden humans, unlimited budgets: how AI demos mislead buyers — and the questions that expose them in five minutes.GuideAI agents in production: what breaksLoops, runaway costs, wrong-record actions, prompt injection and silent failures: how AI agents break in production and the patterns that prevent it.Guide11 ways to cut your LLM billLLM cost optimisation: prompt caching, model routing, shorter context, better retrieval, batching and budgets — checked against evals so quality holds.GuideLLM evals for non-ML teamsHow to evaluate an LLM feature without a data-science team: build a test set, choose metrics, use LLM-as-judge carefully, run evals in CI and read the results.GuideCustomer data in LLMs: GDPR guidePersonal data and LLM APIs: lawful basis, DPAs, transfers, data residency, retention and minimisation — a practical checklist for product teams.GuideEU AI Act for product teamsEU AI Act for teams building on LLMs: risk categories, provider vs deployer, chatbot transparency, high-risk areas and dates after the 2026 AI Omnibus.GuideAn AI support chatbot that doesn’t embarrass youBuild an AI support chatbot customers trust: grounded answers, clear scope, human hand-off, safe actions, abuse protection and honest metrics.GuideDocument AI: extract data from anythingHow modern document AI works: OCR plus LLM extraction, business-rule validation, human review for exceptions and integration with your ERP or CRM.GuideMCP explainedThe Model Context Protocol in plain language: hosts, clients and servers, when to build an MCP server for your systems, and how to secure it.GuideAI for Ukrainian businessesAI for companies in Ukraine: 15 processes to automate this quarter — documents, BAS / 1C, Nova Poshta, Checkbox, support in Ukrainian.GuideAI integration with BAS / 1CConnecting AI to BAS and 1C-based ERPs: integration options, document recognition, reconciliation help, natural-language reports and safe write-back.
Free tools
Free toolAI project effort estimatorFree AI project calculator: six questions → timeline, team, effort in person-weeks and the main cost drivers of your AI project. No signup.Free toolLLM API cost calculatorEstimate the monthly cost of an LLM feature from requests, tokens, model price tiers and prompt caching. Free, in your browser, with your own prices.Free toolVendor lock-in testTwelve questions about code, cloud, access, contracts and docs reveal how locked in you are to your development vendor — with a prioritised fix list.Free toolAI readiness assessmentFree 5-minute AI readiness assessment: data, processes, people, technology and governance — with a radar chart and first steps for weak spots.Free toolRAG vs fine-tuning decision toolUp to four yes/no questions → a recommendation: RAG, fine-tuning, long-context prompting or better prompts, plus the next step to validate it.Free toolProject brief generatorFill in nine fields and get a structured software or AI project brief you can send to any vendor — so the estimates you get back are actually comparable.Free toolAI automation ROI calculatorCalculate hours freed, net monthly saving and payback period for an AI automation — using your own task volumes, costs and a conservative automation share.
Hiring a vendor without regrets
Guide13 red flags your vendor is hiding problemsVague reports, shifting dates, no access to code: 13 signs your outsourced project is in trouble — and what to ask or do about each this week.Guide40 questions to ask an AI vendorDue-diligence checklist for hiring an AI development company: approach, data, quality, security, cost, ownership and team — and what good answers sound like.GuideWho really owns your code?Paying for software doesn’t make it yours. The clauses that decide code ownership: IP assignment, background IP, open source, AI assets, exit terms.GuideFixed price vs T&M vs milestonesWhich contract model protects you? Fixed price, time & materials and milestones compared on risk, flexibility, incentives and hidden costs.GuideHow change requests double budgetsScope creep arrives as dozens of small “quick” changes. How to run change requests that keep budgets honest without slowing the project down.GuideSwitching vendors without a rewriteHow to change development vendors safely: secure assets, plan the handover, transfer knowledge and keep shipping — with a complete handover checklist.GuideHow to write a software briefA practical guide to writing a software or AI project brief: the nine sections that matter, examples of good and bad answers, and a free generator.GuideWhy every estimate is wrongEstimates are forecasts under uncertainty. How to read one, spot hidden assumptions, compare vendors fairly and get forecasts that improve.GuideOutsourcing to Ukraine in 2026Working with Ukrainian engineering teams in 2026: time zones, skills, power and connectivity risks, legal setup and what to ask about continuity.GuideYour MVP is too bigMost MVPs are too big to test anything quickly. How to cut scope: one user, one job, riskiest assumption first, manual before automated.
Comparisons
ComparisonFreelancers vs agency vs in-houseHourly rates hide most of the cost. Freelancers, a development company and an in-house team compared on total cost, speed, risk and control.ComparisonOpenAI vs Azure OpenAI vs AnthropicChoosing an LLM platform: OpenAI, Azure OpenAI, Anthropic (direct, Bedrock, Vertex AI), Gemini and open-weight — by data, procurement and quality.ComparisonVector databases comparedVector stores for RAG: pgvector, Pinecone, Qdrant, Azure AI Search and OpenSearch compared on ops, hybrid search, filtering, scale and cost.ComparisonBuild vs buy AIBuy an AI tool or build your own? Decide by differentiation, data, integration depth, control and total cost — plus the hybrid options.ComparisonNearshore vs offshore vs onshoreOnshore, nearshore and offshore compared on time zones, communication, cost, legal setup and control — and why delivery model beats geography.
Example projects
Example projectSupport copilot for a B2B SaaSIllustrative RAG project: a Zendesk support copilot drafting cited replies from help articles and tickets — discovery, PoC, architecture, lessons.Example projectDocument AI for a distributorIllustrative document AI project: invoices and waybills extracted, matched to purchase orders and posted to the ERP, with human review where it matters.Example projectRescuing a stalled marketplaceIllustrative rescue: a marketplace nine months late, code in the vendor’s account, no tests. How we’d secure assets, audit, decide and ship.
AI by industry
IndustryAI for e-commerceAI for online stores: product content, search, support, returns, reviews and back-office automation — integrated with your platform and carriers.IndustryAI for logisticsPractical AI for logistics and distribution: document processing, shipment status automation, exception handling, customer communication and dispatch support.IndustryAI in fintechAI for fintech and financial services: KYC documents, support copilots, compliance search and risk signals — designed for audit and regulation.IndustryAI in healthcare softwareAI in healthcare software: admin automation, documentation help, patient communication and knowledge search — and where medical-device rules apply.IndustryAI for legal teamsAI for law firms and legal teams: playbook-based contract review, clause search, first drafts and summaries — with citations and confidentiality.IndustryAI features in SaaSHow SaaS companies add AI features customers pay for: choosing features, pricing AI usage, multi-tenant data isolation, cost controls and evaluation in CI.IndustryAI for manufacturingPractical AI for manufacturers: maintenance assistants, quality report analysis, document processing and capturing expert know-how.
Glossary
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