Data Projects

Register Scraping and Data Enrichment Methodology (4 sources)

The objective of this project is to build high-quality databases of educational institutions using each country's official register as the authoritative master source and, where necessary, enrich the records with publicly available contact information extracted from the institutions' official websites. Although each country has its own official register, terminology and technical requirements, the overall methodology is consistent across all projects: 1. Obtain the official register of educational institutions. 2. Build the master database containing all active institutions. 3. Visit each institution's official website, where applicable. 4. Extract publicly available contact information. 5. Select the best contact details according to the predefined rules. 6. Produce one final record for each institution. Country-specific instructions—including official data sources, extraction procedures, field mappings, crawling rules, technical requirements and output specifications—are provided in the corresponding annexes. Each annex forms an integral part of this methodology and shall prevail whenever a country requires procedures that differ from the general approach described above. VALIDATION Before the project is awarded, please submit a validation sample demonstrating that you have fully understood the required methodology. The sample must include 5 records for each of the following sources: • England • Slovakia • Norway • Turkey The sample must follow exactly the same extraction rules, field mappings and output structure that will be used for the final deliverables. Only freelancers whose validation sample meets the required quality standards will be considered for the project award. TIMELINE • Please submit the validation sample as soon as possible. • I will be on holiday from 17 July to 30 July. If you have any questions regarding the methodology or country-specific instructions, please ask them before 17 July, as I may not be available during that period. • The final delivery will be required within 7 calendar days from the project award.

Build webscraper to collect data from outlet menus

I have a list of appr. 50.000 outlets, of which I want to have the menu information scraped cleansed and organised (see FACT DIM below). Assignment is to receive a working and tested code for doing that, perphaps for a smal sample of 100 outlets or so to see that it's working. Lump sum proposal please, needs to be ready asap. Best regards, Sander -------------- CREATE TABLE public.outlet ( outlet_id bigint GENERATED ALWAYS AS IDENTITY NOT NULL, naam text NOT NULL, plaats text, website_url text, segment text, status text NOT NULL DEFAULT 'actief'::text CHECK (status = ANY (ARRAY['actief'::text, 'inactief'::text])), created_at timestamp with time zone NOT NULL DEFAULT now(), updated_at timestamp with time zone NOT NULL DEFAULT now(), CONSTRAINT outlet_pkey PRIMARY KEY (outlet_id) ); CREATE TABLE public.menu_source ( source_id bigint GENERATED ALWAYS AS IDENTITY NOT NULL, outlet_id bigint NOT NULL, pagina_type text, url text NOT NULL, domain text, bestandstype text CHECK (bestandstype = ANY (ARRAY['html'::text, 'pdf'::text, 'image'::text])), confidence real, is_active boolean NOT NULL DEFAULT true, created_at timestamp with time zone NOT NULL DEFAULT now(), CONSTRAINT menu_source_pkey PRIMARY KEY (source_id), CONSTRAINT menu_source_outlet_id_fkey FOREIGN KEY (outlet_id) REFERENCES public.outlet(outlet_id) ); CREATE TABLE public.crawl_run ( run_id bigint GENERATED ALWAYS AS IDENTITY NOT NULL, source_id bigint NOT NULL, crawled_at timestamp with time zone NOT NULL DEFAULT now(), http_status integer, etag text, last_modified text, sha256 text, parse_status text NOT NULL DEFAULT 'pending'::text CHECK (parse_status = ANY (ARRAY['pending'::text, 'ok'::text, 'partial'::text, 'failed'::text, 'not_modified'::text])), parser_version text, raw_ref text, CONSTRAINT crawl_run_pkey PRIMARY KEY (run_id), CONSTRAINT crawl_run_source_id_fkey FOREIGN KEY (source_id) REFERENCES public.menu_source(source_id) ); CREATE TABLE public.menu_item ( menuitem_id bigint GENERATED ALWAYS AS IDENTITY NOT NULL, run_id bigint NOT NULL, categorie text, product text NOT NULL, beschrijving text, prijs numeric, valuta text NOT NULL DEFAULT 'EUR'::text, volume text, merk text, merkeigenaar text, positie integer, confidence real, CONSTRAINT menu_item_pkey PRIMARY KEY (menuitem_id), CONSTRAINT menu_item_run_id_fkey FOREIGN KEY (run_id) REFERENCES public.crawl_run(run_id) ); CREATE TABLE public.change_event ( event_id bigint GENERATED ALWAYS AS IDENTITY NOT NULL, outlet_id bigint NOT NULL, source_id bigint, oud_menuitem_id bigint, nieuw_menuitem_id bigint, detectiedatum timestamp with time zone NOT NULL DEFAULT now(), event_type text NOT NULL CHECK (event_type = ANY (ARRAY['product_toegevoegd'::text, 'product_verwijderd'::text, 'prijs_verhoogd'::text, 'prijs_verlaagd'::text, 'brand_switch'::text, 'menu_redesign'::text])), oude_waarde text, nieuwe_waarde text, ai_interpretatie text, impact text CHECK (impact = ANY (ARRAY['hoog'::text, 'midden'::text, 'laag'::text])), opportunity_score integer CHECK (opportunity_score >= 0 AND opportunity_score <= 100), aanbevolen_actie text, bevestigd_runs integer NOT NULL DEFAULT 1, status text NOT NULL DEFAULT 'nieuw'::text CHECK (status = ANY (ARRAY['nieuw'::text, 'bekeken'::text, 'afgehandeld'::text, 'false_positive'::text])), CONSTRAINT change_event_pkey PRIMARY KEY (event_id), CONSTRAINT change_event_outlet_id_fkey FOREIGN KEY (outlet_id) REFERENCES public.outlet(outlet_id), CONSTRAINT change_event_source_id_fkey FOREIGN KEY (source_id) REFERENCES public.menu_source(source_id), CONSTRAINT change_event_oud_menuitem_id_fkey FOREIGN KEY (oud_menuitem_id) REFERENCES public.menu_item(menuitem_id), CONSTRAINT change_event_nieuw_menuitem_id_fkey FOREIGN KEY (nieuw_menuitem_id) REFERENCES public.menu_item(menuitem_id) );

CRM Data Cleanup Support

We're seeking a freelancer to help organize and clean customer records. The work includes reviewing entries, removing duplicates, correcting formatting, and updating information as instructed. Responsibilities Review customer records Remove duplicate entries Correct data formatting Update information where required If you have strong attention to detail and can deliver accurate work, we'd be happy to hear from you.

Egocentric Video Data Collection – Remote Freelancers Needed

We are looking for reliable freelancers to participate in an Egocentric Video Data Collection project that supports the development of next-generation Artificial Intelligence (AI) and Computer Vision technologies. Participants will record real-life daily activities using an approved smartphone securely attached to a head mount, capturing a first-person (POV) perspective. All recordings will be completed and submitted through a client-provided mobile application. This is a real-world data collection project. We are looking for genuine, natural recordings—not scripted or acted content.

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Data Scraper

I need Desicion maker emails, phone numbers business name, all checked that are working of restaurants in Alicante, Valencia cities in Spain and the small towns around them.

Adobe Lightroom Specialist to create Meta Data

I shoot Bodybuilding shows and need help speeding up my Workflow. I currently use Adobe Lightroom Classic and could use help adding the metadata to each photo. (Name of competitors). It is easy use facial recognition to get most of the meta data. However, When they turn around and view their backs the only reference I have is the numbered button they have on their Bikini/trunks. They typically have two buttons. one on the front and one on the back. I typically have anywhere from 7,000-12,000 pics per show. Anyone out there good at this? Looking for a 2 day turnaround. Please reply with estimate etc. Of course I would have to share the library. Thanks for you time. Price TBD

Icelandic Speakers for Data Audio Collection Project

We’re currently inviting native Icelandic speakers from Iceland to join a paid, fully remote AI audio task. Who we’re looking for: Icelandic speakers from Iceland Task details: 10 short phone calls with an AI bot $18per call ($180 total) Around 30 minutes to complete 100% remote No experience needed How to get started: Complete a quick 30-second Icelandic verification on Click worker (required) Once approved, you’ll get access to the paid audio task

Audience Data Buy (USA) Job Seeker

I am looking for data on 25,000 individuals of Nigerian origin who are currently living in the USA and are interested in transitioning into IT careers. This audience includes nurses, Uber drivers, plumbers, caregivers, warehouse workers, and other professionals from blue-collar backgrounds who are looking to move into the IT industry.

Seeking eCommerce Beta Testers

Beta Tester - Optagen Portal & Integrations What you’re testing The Optagen portal lets you manage multiple stores by bringing together data from your commerce, analytics, accounting, inventory, and CRM systems. It creates a single ranked action list, with each recommendation labeled for trust and checked against real results. We need beta testers to use the portal with real store data and identify what breaks, what’s slow, what’s missing, and what doesn’t match reality. Integration coverage required You will test syncing and data accuracy across these integrations: Commerce platforms: Shopify, BigCommerce, WooCommerce, Etsy Analytics: Google Analytics 4, Search Console Shipping/3PL: ShipBob, ShipStation, Easyship Inventory systems: Cin7, Katana Accounting: QuickBooks, Xero Marketing/CRM: Klaviyo You don’t need to use every integration—just test the ones you already use. We’re aiming for each tester to cover at least 3 or 4 integrations from different categories. What we’re asking 1. Sync completeness: Check if all the expected fields from each integration show up in the portal. Are SKU, pricing, margin, sales, traffic, inventory, and competitor data there? 2. Refresh latency: See how long it takes for changes in your source system (like a price update in Shopify or a GA4 event) to show up in the ranked plan. 3. Data accuracy: Choose 5 to 10 data points you can check in both your source system and Optagen. Do they match? 4. Signal read accuracy: The portal calculates metrics such as AI visibility, SKU margins, demand signals, returns concentration, pricing elasticity, and competitor share of voice. Check these against your store. Do they make sense? Can you find the data sources if you look for them? 5. Ranked plan stability: Run the same store scan twice in one week. Does the ranked plan update based on new data, or does it stay the same? Are the revenue-impact numbers realistic? What we’re not asking * Testing the governed execution agent (scheduled to ship later; currently in development) * Load testing or scale testing * Security testing or pen testing * UX/design feedback (we’ll gather that separately) Timeline and access * Beta runs from [DATE] to [DATE] * You’ll get portal access for your own stores, using your real data—not test data. * We’ll keep an eye on logs and collect diagnostics if something fails. Please report any issues as they happen via a feedback button. * We’ll have a weekly sync call to talk about any blockers or patterns you notice. Who should apply * You run 1-5 stores across 2+ of these platforms. * You can verify data accuracy (you know your actual margins, traffic, and sales numbers) * You’re willing to spend 2-4 hours per week auditing sync health and data correctness. * You’re okay with bugs and incomplete features since this is a beta test. When you apply, please indicate: * Which platforms you currently use (Shopify, BigCommerce, WooCommerce, Etsy etc.) * Rough store size (monthly revenue or annual, average order value, SKU count) * Any specific data quality concerns you have with your current setup

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Yorkshire Data Scraper

We are looking to purchase or commission an up-to-date, high-quality B2B marketing database covering Yorkshire and surrounding areas The data will be used to market Material Handling Equipment, Forklift Trucks, Warehouse Equipment, Scrubber Dryers and Industrial Sweepers, so the data must be relevant to companies with factories, warehouses, depots, production sites, industrial premises or operational facilities We are not looking for a basic scraped company list. We require verified, marketing-ready data with named contacts and valid emails wherever possible Include companies located in the following postcode areas: BB, BD, BL, HG, LS, HX, HD, WF, DN, S, SK The address should relate to the actual trading, manufacturing, warehouse, depot or operational site, not just a registered office address where possible. Include companies in the following sectors: 10 – Manufacture of food products 11 – Manufacture of beverages 13 – Manufacture of textiles 14 – Manufacture of wearing apparel 15 – Manufacture of leather and related products 16 – Manufacture of wood and products of wood and cork, except furniture 17 – Manufacture of paper and paper products 18 – Printing and reproduction of recorded media 19 – Manufacture of coke and refined petroleum products 20 – Manufacture of chemicals and chemical products 21 – Manufacture of pharmaceutical products and preparations 22 – Manufacture of rubber and plastic products 23 – Manufacture of other non-metallic mineral products 24 – Manufacture of basic metals 25 – Manufacture of fabricated metal products, except machinery and equipment 26 – Manufacture of computer, electronic and optical products 27 – Manufacture of electrical equipment 28 – Manufacture of machinery and equipment n.e.c. 29 – Manufacture of motor vehicles, trailers and semi-trailers 30 – Manufacture of other transport equipment 31 – Manufacture of furniture 38 – Waste collection, treatment and disposal activities; materials recovery 41 – Construction of buildings 52 – Warehousing and support activities for transportation We want to focus mainly on companies with 1–199 employees Please include employee banding, for example: 1–10 11–25 26–50 51–100 101–199 200+, only if highly relevant For every company, we require the following where available: Company type/industry Company name SIC code Website Employee banding Site address split into address line 1, line 2, line 3, town/city, county and postcode Postcode area Company telephone number Company LinkedIn page Date verified Contact Requirements We require named decision-maker contacts wherever possible. Priority contacts include: Operations Manager Warehouse Manager Purchasing Manager Procurement Manager Facilities Manager Site Manager Production Manager Logistics Manager Managing Director Director General Manager For each contact, please provide: Contact name Job title Direct email address Generic email address, only where no direct email is available Email type: Direct or Generic Email validation status Landline number Direct dial, where available Mobile number, where available Contact LinkedIn profile Date contact was last verified Email Quality Requirements Valid, up-to-date emails are essential. Direct business emails are strongly preferred. Generic emails should only be used where a verified named contact email cannot be found. Please separate direct and generic emails into separate columns. Do not mix them in the same field. We do not want large volumes of guessed, invalid, risky or unverified email addresses. Please confirm what email validation method or tool has been used and include the validation result in the data. Acceptable generic emails, only where direct contacts are unavailable, may include: info@ sales@ enquiries@ purchasing@ procurement@ operations@ Please do not include personal email addresses such as Gmail, Outlook, Hotmail or Yahoo. The data must be: Recently verified Relevant to the requested postcode areas Relevant to the requested industries Deduplicated Suitable for B2B marketing use Free from dormant or dissolved companies Free from irrelevant businesses Focused on genuine operating companies Accurate and cleanly formatted Please do not apply if you are only able to provide basic scraped Companies House data without named contacts and verified emails. Before placing the full order, please provide a sample of 50–100 records. The sample should include a mix of postcode areas, sectors, employee sizes, direct contacts and generic contacts where direct emails are unavailable. The sample will be checked for relevance, accuracy, direct email quality, duplicate records, address quality and suitability for marketing material handling and floor care equipment. We expect there to be over **2,500 companies** matching the requested criteria. Please provide an estimated breakdown by: Postcode area Industry / SIC code Employee banding Number of direct contacts Number of generic contacts Number of validated emails

Cold Call Insurance Data

I am looking for an experienced telemarketer to dial B2C data that will be provided. I would like to trial 2000 records to see how they can perform. Data capture will need to include; Insured, Uninsured, Insured through work then insurance provider i.e AXA, Aviva etc then renewal date and interested not interested. I am a broker in Private health insurance so will all need to be compliant etc. Of course i'd love everyone to be ready to discuss, transferred or appointment to be booked but as long as we can cleanse the data that is my main focus at this stage. if successful this will be an ongoing project for the foreseeable. This project is for real humans only with clear English as this is a very sceptical industry and I do not feel it would be very successful otherwise. Please offer a fair price on the service and happy for 2 prices, one for a trial and one for an ongoing contract I look forward to hearing from you Ben

Data Center - 2D and 3D design

I need a designer that is specialised in the design of Data Center (20MW upto 150MW). Trackrecord and esperience necessary.

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Malaysia Freelancers Needed for Video Collection Project

We are looking for reliable freelancers to participate in an Egocentric Video Data Collection project that supports the development of next-generation Artificial Intelligence (AI) and Computer Vision technologies. Participants will record real-life daily activities using an approved smartphone securely attached to a head mount, capturing a first-person (POV) perspective. All recordings will be completed and submitted through a client-provided mobile application. This is a real-world data collection project. We are looking for genuine, natural recordings—not scripted or acted content.

MailChimp Email Newsletter Templates

I need a flexible designer to work with our small NGO on a range of newsletters and fundraising campaigns. My immediate need is for a simple newsletter with a donate option, a data clean up / unsubscribe option and to go out to around 1,000 contacts.

Product Catalog Spreadsheet Data Cleansing Description

Looking for a meticulous data entry freelancer to clean and format an existing product catalog spreadsheet for an internal review. All data is fully provided; no external sourcing or account creation is required. Responsibilities Organize product descriptions into correct columns. Clean up formatting and align pricing fields. Identify and remove duplicate rows. A Note for Applicants If you are detail-oriented and enjoy turning messy data into a structured spreadsheet, please send through your proposal. Looking forward to your applications!

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Commodity Trading CRM

Seeking an experienced developer familiar with Replit to support and finalize a bespoke Commodity Trading CRM for international markets. The product, initiated on Replit, requires assistance with feature completion, integration, data workflows, user interface refinement, and performance optimization. Ideal candidate will demonstrate Replit proficiency, backend and frontend competence, familiarity with trading workflows, secure data handling, and a collaborative approach to meet delivery timelines and quality standards.

Data Scraping - Competitor feedback

I need someone who can look at competitor recommendation websites for certain businesses and then work out who their customers are from people who have left comments of that business. This role is best suited to someone in the UK or at least very familiar with what names are common / uncommon in the UK. There will be names that are too generic and you cannot find the exact person for the business on companies house (like John Smith, Adam Cox, Joe Frost) , so they can be skipped. I need you to find exact businesses and be 100% sure that the company you find belongs to the person who left the comment. This task will take accuracy and care, rather than quickly gathering as much data that wont be needed. The company on Companies House needs to show it is ACTIVE, not anything else. Otherwise move on to the next record. EXAMPLE For example there is a comment from someone called Louise Lamberti (which isnt a very common name) Then i searched the name on Companies House and find the company she has: https://find-and-update.company-information.service.gov.uk/officers/0jr3CzJOVyJKznJUNuQQgwaAZH8/appointments There is no one else with this name as an Officer on Companies House so i am pretty sure this is the company it relates to. Then i need someone to gather as much information as possible on the business which the attached spreadsheet. I need named business email addresses and contact numbers - no personal email addresses! Tab 1 holds information for the business that we need Tab 2 are the different company names that you can search their feedback If you need more clarification please let me know. Looking for someone to work on this for an ongoing basis - will pay £10 per hour and expect to get around 40 records per hour. PLEASE COULD YOU SEND ME AN EXAMPLE ON THE ATTACHED SPREADSHEET OF 2 RECORDS THAT YOU FIND SO I CAN TEST THE QUALITY OF YOUR WORK BEFORE I ACCEPT. Happy to go through a video call to explain in more detail if this is required. £10 per 100 records - ongoing project

Build a Secure Live AI Research Data Processing Prototype

Rapid Low-Code AI Document-Parsing Web Prototype (Secure Cloud Tenant) in Microsoft Copilot Studio / Azure OpenAI Project Overview: I need a highly concise, working prototype of a secure web application interface. The sole purpose of this app is to demonstrate a secure, live text-processing pipeline during a brief stakeholder review. It must ingest a raw text document/dataset, simulate a structured evaluation process against a pre-set compliance rubric, and dynamically display an optimization analytics page. Key Requirements to Implement: 1. Secure File Upload Interface A minimal, clean user interface with a file drop zone labeled: "Secure Sandbox: Upload Manuscript / Dataset Draft (PDF, DOCX, or CSV)". A secondary text field labeled: "Alternative Manual Input: Paste Methodology / Text Details". A dropdown parameter selector: [Parameter Group A / Baseline Metrics Checklist]. 2. Localized Governance Engine Setup Connect this frontend interface securely to an LLM endpoint (via Microsoft Copilot Studio, Azure OpenAI Studio template, or a standard private API pipeline). Define system prompts to parse the document's sections (checking for structural clarity, data mapping consistency, and alignment with baseline formatting rules). 3. Dynamic Output & Accountability Dashboard Upon document submission, the UI must refresh dynamically to show: Maturity / Verification Score: A clean progress gauge (e.g., Ecosystem Readiness Level: 84%). Compliance Rules Checklist: Visual indicators displaying: [Passed] Citation & Data Anonymization Check [Passed] Methodological Parameter Scope [Warning] Formatting Ambiguity Detected in Section 3 Actionable Next Steps: A generated text box detailing exactly what parameters need optimization. Technical Constraints: Must be deployed on a functional, live preview web URL so I can interact with it live during the meeting. Data privacy configuration must be explicitly set to ensure no data processed is utilized for public model training datasets. Important Fail-Safe: Hardcode a single specific fallback template path into the interface so that if the live internet connection fluctuates during the review, the target upload file will immediately trigger the exact correct completed dashboard layout cleanly.

Secondary school contact data gap-fill

I have a spreadsheet of 67 secondary UK schools where I need to identify, by name, the people who sit in six specific roles at each school — and find their verified work email address. You will be filling in a pre-built spreadsheet I provide. Most of the work is done — the school list, websites, addresses, phone numbers and which roles still need finding are all already mapped. Your job is to look up the names and verify the emails. The 6 roles per school Head Teacher Cover Manager (the day-to-day supply booker) School Business Manager (SBM) Head Teacher's PA / Office Manager Deputy or Assistant Head (with a staffing or cover portfolio if possible) SENCO (Special Educational Needs Coordinator) What you'll deliver The same spreadsheet I send you, with every red "FIND" cell filled in using one of three formats: Verified name | verified email — for example: Sample Postholder | s.postholder@exampleschool.org.uk NAME FOUND — EMAIL NOT VERIFIED | [name] — if you can identify the postholder but cannot get a verified email NOT FOUND — if no current postholder can be confirmed after a proper search There are approximately 240 individual cells to fill across the 67 schools. Not every school needs all 6 — some roles are already covered and marked HAVE in green; just skip those. You will need to have access to a range of software and resources to support you as these email addresses are not simply on the school website - therefore research and effort will be required to find and source correct validated emails.

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UK Solicitor ONLY: Food app T&Cs, privacy & telemetry

I am launching a consumer mobile app in the food and recipe space, helping people reduce food waste and discover recipes. I need comprehensive legal documentation and data protection advice before going live. Full technical details will be shared once engaged. ------------------------------------------------- 1. PRIVACY POLICY, TERMS & CONDITIONS, AND TERMS OF USE Full, production-ready documents suitable for App Store (Apple) and Google Play submission, covering a global user base. Must address: - Data collected, purpose, and retention - Lawful basis for processing across all major jurisdictions (UK, EEA, US, and a framework for the rest of the world) - User rights (access, erasure, portability, objection) - Third-party processors and data sharing - Cookie/tracking equivalents in a mobile context - Minimum age requirements across jurisdictions ------------------------------------------------- 2. TELEMETRY AND DATA COLLECTION ADVICE The app collects behavioural telemetry linked to a pseudonymous per-install identifier (no name or email stored). I need written advice covering: - What I can legally collect, and on what lawful basis, across different regulatory regimes (UK GDPR, EU GDPR, CCPA/CPRA, and any other material jurisdictions) - Legitimate interest vs. consent, when each applies and how to document it - Anonymisation thresholds, what level of aggregation (e.g. on-device aggregation, k-anonymity, category-level bucketing) takes data outside scope entirely, and the equivalent thresholds under CCPA and other regimes - Commercial data licensing, whether and how anonymised or aggregated data can be sold or licensed to third parties without consent obligations, and what conditions must be met per jurisdiction - Children's data obligations by jurisdiction (COPPA, Article 8 UK/EU GDPR, etc.) - Proportionate and defensible retention periods ------------------------------------------------- 3. DPIA REVIEW Review and sign off a completed draft DPIA for the telemetry feature. Full document provided once engaged. ------------------------------------------------- WHAT I AM NOT LOOKING FOR - Generic template documents - Advice limited to UK/EU only, global coverage is a requirement - Junior associate work without senior oversight ------------------------------------------------- DELIVERABLES - Production-ready Privacy Policy (global scope) - Production-ready Terms & Conditions and Terms of Use - Written advice note on telemetry, anonymisation thresholds, and commercial data licensing by jurisdiction - DPIA sign-off or marked-up revisions ------------------------------------------------- BEFORE I ENGAGE, PLEASE PROVIDE Proof of qualification - SRA number or equivalent with current practising certificate Relevant experience - examples of privacy policies or data protection advice delivered for consumer mobile or digital products (anonymised references or case studies are fine) Data protection specialism - confirmation this is a primary part of your practice, not an occasional add-on; CIPP/E or BCS Practitioner Certificate in Data Protection preferred Global coverage - confirm you can advise substantively on UK GDPR, EU GDPR, and US (CCPA/CPRA) at minimum, and state clearly which other jurisdictions (Canada, Australia, Brazil etc.) you can or cannot cover Turnaround - this is blocking a production release, please state realistic timelines upfront