Industry solution
From sequencing run to field trial, keep every sample, result and promise traceable
Sequencing runs, analysis and storage, consented data access, partner milestones and trait trials, designed to connect in one workspace.
The problem
Genomics teams run sample sheets, analysis, storage, consent records, partner deliverables and field trials in separate spreadsheets and systems, so one index clash or one withdrawn consent spreads before anyone can see how far.
A modern biotech runs on throughput. Libraries are pooled onto flow cells by the hundred, analysis pipelines turn raw reads into variant calls and expression tables, and the data grows faster than any budget line. Much of that flow is still stitched together by hand: sample sheets built in spreadsheets, run quality checked in instrument folders, pipeline versions remembered rather than recorded, and storage spread across an on-premises cluster and several cloud accounts, with no one sure what each terabyte belongs to.
Around the data sit obligations that do not forgive gaps. Human genomic data carries the consent each participant gave, and that consent differs by form version, by use and by partner. Collaborations with pharmaceutical and seed partners pay on milestones and fund an agreed number of scientists, and partners expect evidence rather than slides. Agricultural trait programs run regulated field trials whose permits require isolation from compatible crops, a controlled harvest and every seed packet accounted for.
The pressure lands on a handful of people: the core manager who learns of a failed lane when submitters start emailing, the bioinformatics lead asked to re-run a thousand samples on a new reference build, the data steward handling a withdrawal in the same week as two access requests, the alliance manager preparing a steering committee, and the trials manager racing rain to a harvest window. Each is solving a problem that crosses teams with a tool built for one.
Sequencing core manager
Clean sample sheets before a run is loaded, lane quality visible the morning a run finishes, and honest turnaround promises to every submitter.
Head of bioinformatics
Every deliverable traceable to its pipeline version, reference build and input reads, and a storage and compute bill that maps to projects.
Data governance lead / access committee chair
Access decisions that follow each participant's consent, withdrawals honored everywhere, and a clear record of who approved what and why.
Alliance or business development manager
Milestones tied to real evidence, steering committee updates without a scramble, and FTE reports that stand up to the partner's questions.
Field trials and stewardship manager
Plot data captured at the edge of the field, every seed packet accounted for, and harvest crews trained on the permit conditions before they start.
Chief operating or scientific officer
One connected view across lab, data, partners and field, fewer late surprises, and no new single-purpose tool for each team.
A day in the life
Maren runs the operational side of a company that sequences for its own programs and for partners. Halden Ridge has a sequencing core with two high-output sequencers, a bioinformatics team working on an on-premises cluster and in the cloud, a population genomics program built with two hospital partners, a drug-target collaboration with a pharmaceutical partner, and a drought-tolerance sorghum trait in trials at five sites. This is one week in late September, when harvest, a steering committee and quarter-end arrive together.
Monday, 6:50 a.m.
Kofi Mensah, who runs the sequencing core, opens the overnight demultiplexing report: lanes 1, 2 and 4 are done, but lane 3 stopped on an index collision. By 7:30 the pharmaceutical partner's project coordinator is asking where the target validation libraries are. Kofi traces it to a pooling plan copied from last month's sheet: two libraries from different projects, both prepared with the same dual-index pair, went onto lane 3, and their reads cannot be separated. He forwards the report to Maren. Nobody can yet say whether the two libraries have enough material left to re-pool or need a new prep.
How this is solved: Index clashes and failed lanes found after the runTuesday, 9:30 a.m.
The pharmaceutical partner asks for its 1,200 exomes to be re-called on the current reference build. Diego Ferreira, who leads bioinformatics, cannot say which version of the analysis produced last year's delivered variant files, and the raw reads and half of the aligned reads moved to archive storage in the spring. The same morning, the cloud bill shows a variant-calling job that failed and retried all weekend on large machines, and a finance analyst asks Maren who owns 300 terabytes of files labeled only tmp.
How this is solved: Re-analysis requests against data nobody can place or priceWednesday, 11:15 a.m.
Hana Kobayashi, the data governance lead, gets a notice from a hospital partner: a participant in the population cohort has withdrawn consent. An hour later, the data access committee, which Maren sits on, receives two requests for the cohort's variant data, one from a university group and one from the pharmaceutical partner. Participants signed three versions of the consent form over six years, and only some allow commercial use. Hana's spreadsheet of consent codes was last reconciled in June.
How this is solved: Consent versions, withdrawals and access to genomic dataThursday, 3:00 p.m.
Jonah Whitfield, the alliance manager for the drug-target collaboration, starts the joint steering committee deck with Maren. Milestone 3, a validated package for three targets, is due October 31 and carries a milestone payment. Monday's lane 3 collision pushed the validation sequencing for target 2 back a week, and Jonah hears about it from a scientist in the hallway. The partner also wants the quarterly FTE report: the contract funds six full-time equivalents, but two scientists spent August on the government innovation grant.
How this is solved: Milestone payments and funded FTEs rebuilt from memoryFriday, 7:15 a.m.
Ruth Alemayehu, who manages the trait trials, sees heavy rain forecast for Saturday at site 3, where the drought-tolerance plots are ready to harvest, and calls Maren to bring the harvest forward to Friday afternoon. The permit requires the trait plots to be harvested separately, the material devitalized or returned, and every seed packet reconciled. Plot weights from sites 1 and 2 are still on two tablets that have had no signal, the seed log shows two packets unaccounted for, and one harvest crew member's stewardship training lapsed in August.
How this is solved: Trait trials, harvest windows and seed that must be accounted forNone of these moments is unusual for a genomics company; together they make an ordinary week. What makes them expensive is that the facts behind each one live in a different system. The solution below is designed so the sample, the run, the data, the consent, the people, the partner commitment and the field plot sit in connected products on one workspace, and each hand-off happens once.
Challenges and how they are solved
Each challenge shows the problem as it happens, how the products are designed to hand work to each other, and the concepts that illustrate it. Share any challenge on its own.
Answers are in plain business terms. Choose Technical, or open any technical detail, to see how it works under the hood.
Challenge 1 of 5
Sample sheets and pooling plans are assembled by hand from submission spreadsheets, and index pairs are picked from memory or copied from last month's sheet. When two libraries on the same lane carry the same index pair, the clash only shows up after the run: demultiplexing stops on an index collision, or the two libraries' reads cannot be told apart, and the core usually finds out when submitters start asking for their data. Run quality, from yield to the share of bases at Q30 or better, sits in instrument output folders and a weekly spreadsheet, so nobody can quickly say which samples, projects and partners are affected, or which libraries have enough material left to re-pool.
A lane's data is held up while the sheet is rebuilt, the clashing libraries must be sequenced again, turnaround promises to teams and partners slip, and re-runs use reagents and flow cell space planned for other work.
LabsOfScience is designed to check every lane's index barcodes before the sequencer is loaded, so a clash is caught at the bench, not after the run. When a run finishes, FluidGrids passes the lane results along, BigConsole shows one live board of lane quality, and the core manager and affected teams hear the same morning, with a list of libraries that can be re-pooled.
Technical detail
Four hand-offs. First, LabsOfScience is designed to hold each submission's libraries as tracked samples with remaining volume, and its new run sheet is designed to check sheet indexes against each library's record, plus clashes and near-matches on a lane, before the sheet is locked. Second, when the sequencer finishes, a FluidGrids workflow started by a webhook or a scheduled check is designed to read the demultiplexing summary, apply pass and fail rules per lane, and write lane results back to the LabsOfScience run. Third, the same workflow pushes per-lane quality into a BigConsole data sink, the documented FluidGrids-to-BigConsole path, where the core's console shows yield, Q30 and undetermined reads by lane, instrument and project. Fourth, BigConsole alert rules on that sink are designed to notify the core manager and each affected submitter, while the run sheet lists which libraries can be re-pooled and which need a new prep.
Designed so index clashes are caught before a flow cell is loaded, and a bad lane becomes a same-morning re-pool list instead of a week of emails.
LabsOfScience
Is designed to check each lane's dual-index pairs against library records and for clashes before the sheet is locked, then show per-lane yield, Q30 and undetermined reads with a re-pool list.
Works with FluidGrids, BigConsole
FluidGrids
Is designed to carry each finished run's lane results from the demultiplexing summary into a BigConsole data sink that feeds the sequencing core's live console.
BigConsole
Is designed to hold alert rules on the lane-quality sink, such as undetermined reads above the core's limit, so the right people hear the morning a run finishes.
Challenge 2 of 5
The analysis software has changed versions several times, and so has the reference genome build. Delivered variant files rarely record which analysis version, reference build and input reads produced them. Raw and aligned reads sit across an on-premises cluster and several cloud storage accounts, some already moved to an archive tier where bringing data back costs money and takes days. Hundreds of terabytes of intermediate files carry no project or partner label, and a failed job can retry all weekend on large machines before anyone looks at the bill.
Re-analysis is quoted blind, storage costs climb every month with no project to charge them to, and the team cannot show a partner that the retention terms in its contract are being kept.
LabsOfScience keeps a record of which analysis version, reference genome and exact reads produced every result. AdapterCloud is designed to show where that data sits, what each project and partner's share costs, what restoring archived reads would cost, and which files have no owner. Data a partner contract says to keep is flagged before anyone deletes it, and a runaway job is flagged to whoever started it.
Technical detail
LabsOfScience is designed to be the record of the analysis: each pipeline run is pinned to an exact, checksummed version of the input reads and records the pipeline version, engine and parameters, including the reference build, so a delivered variant file traces back to the run that made it. Project and partner codes from those runs are designed to hand off to AdapterCloud as tags. AdapterCloud is designed to discover storage and compute across the cloud accounts and the cluster, attribute cost to each project and partner code, and flag a runaway job, such as a weekend retry loop, to its owner. Its new genomics storage view is designed to show FASTQ, BAM/CRAM and VCF storage by project and tier, cost per sample from LabsOfScience sample counts, the cost and time to restore archived reads for a re-call, and to flag storage under a partner retention term if it is scheduled for deletion before its date.
Designed so a re-analysis request becomes a scoped, priced plan, and every terabyte has a project, a partner and a retention rule.
LabsOfScience
Records each variant-calling run against a pinned version of the sequencing reads, with its pipeline version, status and log, so a delivered variant file traces to the run that produced it.
AdapterCloud
Is designed to show FASTQ, BAM/CRAM and VCF storage by project, partner and tier, with cost per sample, restore estimates for archived reads and retention-term checks.
Works with LabsOfScience
AdapterCloud
Is designed to attribute cluster hours and cloud spend to each project and partner code, as it does for research awards, and flag a runaway job such as a weekend retry loop to its owner.
Challenge 3 of 5
Participants in a population cohort signed different versions of the consent form over the years. Some allow general research use, some allow research on one disease area only, and some exclude commercial use. Consent status lives in each hospital partner's register, reaches the company as periodic extracts, and ends up in a spreadsheet the governance team reconciles by hand. The data access committee reviews requests by email, and approved data often leaves as exported files that cannot be recalled. When a participant withdraws, nobody can be sure their data stays out of the next release or partner analysis.
The company risks sharing data beyond what participants agreed to, partners wait weeks for decisions, and the hospitals and participants who make the program possible lose confidence in it.
SemanticFed is designed to read each participant's consent where the hospital keeps it, so a partner only sees people whose consent covers that use. The data access committee sees each request beside how many participants qualify, and nothing opens until a member approves it, with an end date. When someone withdraws, FluidGrids tells the committee, flags earlier releases and asks for their samples to be held.
Technical detail
SemanticFed is designed to model the cohort across its sources where they are kept: each hospital partner's consent register, or the consent extract it shares, and the variant store. AdapterCloud is designed to pass the variant store's location, region and owner so SemanticFed registers it with its residency known. Consent codes are designed to become access policies: a row filter would let a requester's role see only participants whose consent permits that use, with direct identifiers denied by column. The new review screen is designed to check each request's stated use against consent versions, count eligible participants, and draft the policy inactive until a committee member approves it with an end date. Because consent is read in place, a withdrawal is meant to drop that participant from eligible rows on the next request. FluidGrids is designed to route the withdrawal notice by rule: notify the committee, flag earlier releases and request a LabsOfScience sample hold.
Designed so every shared row sits inside a participant's consent, every access decision carries a named approver and an end date, and a withdrawal reaches every place it needs to.
SemanticFed
Is designed to line up each access request against the cohort's consent versions, show eligible participant counts, and hold the drafted policy inactive until a committee member approves it.
Works with FluidGrids, LabsOfScience
SemanticFed
Surfaces direct identifiers such as date of birth and hospital number as proposed deny rules that stay inactive until a person approves and activates them.
FluidGrids
Is designed to route a hospital's consent-withdrawal notice by rule: notify the committee, flag past releases that included the participant and request a sample hold.
Challenge 4 of 5
A drug-target collaboration pays on milestones with acceptance criteria written into the contract, funds an agreed number of full-time equivalents (FTEs) at a set annual rate, and reviews progress at a joint steering committee. The alliance manager builds each committee deck from slides, email threads and hallway updates, so a slip in the lab reaches them late. The quarterly FTE report is assembled from timesheets that do not separate collaboration work from internal programs, while a government innovation grant with its own milestones competes for the same scientists.
Milestone payments slip or are disputed, FTE reports that cannot be backed up strain the partner relationship, and the steering committee hears bad news after it could have been managed.
PlanMagnet is designed to put each partner milestone, its acceptance terms and its payment on one page, next to the lab work that proves it. CrewFoundry supplies who worked on the collaboration and their approved hours, so the full-time equivalent (FTE) report starts from real time rather than estimates. When a lab delay threatens a milestone, the alliance manager sees it the same week, not at the steering committee.
Technical detail
PlanMagnet is designed to hold the collaboration as a project: each milestone with its acceptance criteria, due date and committee date, the payment amount and status recorded against it, and each deliverable linked to the LabsOfScience experiments and data versions that form its evidence. Consent-checked cohort evidence from SemanticFed is designed to link to Milestone 3's evidence package. Through the documented PlanMagnet and CrewFoundry capacity integration, planned FTEs are checked against each scientist's availability; approved CrewFoundry timesheets, attributed to the collaboration project, are designed to hand off to the tracker as actual effort by month, flagging a gap before the quarterly report. The government innovation grant runs as a second project in PlanMagnet's grant aims and deliverables tracker, drawing on the same people, and a delay recorded against a LabsOfScience run is designed to surface on the milestone it threatens.
Designed so a steering committee sees slips while they can still be managed, and every FTE figure in a partner report ties back to approved time.
PlanMagnet
Is designed to show each collaboration milestone with acceptance criteria, payment status and linked evidence, beside committed FTEs and actual effort from approved CrewFoundry hours.
Works with CrewFoundry, LabsOfScience, SemanticFed
CrewFoundry
Holds weekly timesheets with approval status, the approved hours behind each scientist's effort on the collaboration and on internal programs.
PlanMagnet
Is designed to run the government innovation grant beside the collaboration, with aims, deliverables, LabsOfScience experiments and CrewFoundry effort on one timeline.
Challenge 5 of 5
A drought-tolerance trait is in regulated trials at five sites run with cooperating growers. Each site has a randomized plot layout of trait entries and checks, planted from numbered seed packets. Permit conditions require isolation from compatible crops, inspections at flowering, a separate harvest of trait plots, devitalization or return of the harvested material, a reconciliation of every packet and monitoring for volunteer plants the next season. Stand counts, flowering dates and plot weights are written on paper or on tablets with no signal, and harvest crews change from week to week.
One unreconciled seed packet or an untrained crew member can put a permit and the trait program at risk, and plot data entered late or against the wrong plot weakens a season that cannot be repeated.
Healthy Bowl is designed to let field technicians record plot counts, flowering dates and harvest weights on a tablet with no signal and send them later. One board shows every plot, the permit tasks due at each site, where every seed packet ended up and the rain outlook. CrewFoundry shows who has current stewardship training, so only cleared people join a trait harvest.
Technical detail
Healthy Bowl is designed to hold each trial site as a farm with its fields and plots, planting plans and harvest records, and to let technicians record stand counts, flowering dates and plot weights with a photo and location stamp where there is no signal; offline field capture is on its roadmap. The new trial stewardship board is designed to show every plot by entry, the permit tasks due at each site, seed packets shipped, planted, returned and devitalized, and the farm's own forecast alerts for the harvest window. CrewFoundry holds stewardship training as a learning path with completion tracking and is designed to show who is trained on the current version of each stewardship procedure; the board is designed to read that record so only cleared crew members join a trait-plot harvest. Harvested plot data is designed to hand off to LabsOfScience as a new version of the trial's data, where each site is a run of the multi-location experiment.
Designed so every plot's data lands against the right entry, every seed packet has a recorded end, and only cleared crews touch trait plots.
Healthy Bowl
Is designed to show each site's plots by entry, open permit tasks, seed packet reconciliation and the harvest-window forecast, with CrewFoundry training clearance for each crew member.
Works with CrewFoundry, LabsOfScience
Healthy Bowl
Is designed to let technicians record plot observations and harvest weights with a photo and location stamp where there is no signal, holding them until the tablet reconnects.
CrewFoundry
Is designed to show who is trained on the current version of each stewardship procedure, flag anyone not yet cleared, and assign retraining when a procedure changes.
How it fits together
Each product does one job and hands its output to the next, with one shared sign-in and one record of who did what. The hand-offs below are how the products are designed to work together, following partner samples from the run sheet through the sequencing core and analysis to consented evidence for a milestone.
To FluidGrids: The final run sheet, so results match the right samples
To BigConsole: Quality results for every lane of the run
To LabsOfScience: Good lanes released for analysis, clashing libraries queued to re-run
To AdapterCloud: Project and partner labels for the storage each run used
To SemanticFed: Where the shared variant data lives and who owns it
To PlanMagnet: Consent-checked evidence for the partner's milestone
To CrewFoundry: Planned staff time for everyone on the collaboration
Step 1 of 8: Lock the run sheet
Technical detail
Products in this solution
Samples, run sheets, analysis runs and trial data
It is designed to keep one record from sample to result: every library, every run, each locked copy of the data and every analysis, so the team can always say what produced a result.
Technical detail
Its inventory items with quantity and lot, auto-numbered runs, checksummed dataset versions and pipeline runs pinned to an exact data version, with sample tracking on its roadmap, give the sequencing core and bioinformatics team one record from library to variant file.
Run checks and consent-withdrawal routing
It passes the news along: it is designed to check each finished run against the core's rules and make sure a consent withdrawal reaches everyone who has to act on it.
Technical detail
Webhook and schedule triggers, if/switch branching and its documented data sinks into BigConsole let it check each finished run, and it is designed to route consent withdrawals to everyone who has to act.
Sequencing core quality console
It gives the core manager one live board of lane quality and turnaround, and is designed to warn the right people when a lane falls short.
Technical detail
Data sinks fed by FluidGrids and interactive consoles give the core manager a live view of lane quality and turnaround by instrument and project, with alert rules designed to warn the right people.
Storage and compute inventory, cost and retention
It is designed to show where all the sequencing data sits across the cluster and the cloud, what each project's share costs, and which files nobody owns yet.
Technical detail
Discovery across cloud accounts and clusters, cost records attached to the same resources, and tagging and compliance policies with tracked violations are designed to map every terabyte to a project and partner and flag retention terms at risk.
Consent-scoped access to cohort data
It is designed to let approved partners work with cohort data only where each participant's consent allows, reading consent where the hospital keeps it rather than copying it.
Technical detail
Designed to read partner consent registers or shared extracts and the variant store where they are kept, with row and column access policies that a person approves, it fits consent codes that differ by participant and by use.
Partner and grant milestones
It keeps partner and grant milestones next to the lab work that proves them, and checks planned staff time against what people can actually give.
Technical detail
Milestones linked to the work that delivers them, payment terms it is designed to carry on each milestone, and its documented CrewFoundry capacity integration fit collaborations that pay on evidence and fund an agreed number of FTEs.
Allocation, timesheets and stewardship training
It holds who works on which program and their approved hours, and is designed to show who has current stewardship training before they join a trait harvest.
Technical detail
People-to-project allocation, time entries with project attribution and approval, and learning paths with completion tracking are designed to supply the actual effort behind FTE reports and the training record behind every harvest crew.
Trial sites, plots and field stewardship
It is where trial sites, plots and harvests live, and it is designed to work at the edge of a field with no signal, so plot data is recorded where it happens.
Technical detail
Its farm, field, crop and harvest records, live weather alerts and compliance records, with offline field capture on its roadmap, fit multi-site trials run with cooperating growers.
Burdenoff Workspaces is the shared foundation: one sign-on for staff and the partners you invite, role-based access that follows people across every product, one audit trail for runs, consent decisions and milestones, and one bill across the products you adopt.
Concept gallery
15 concepts from 8 products. Each one links to its own page on the product's website, and every view has a link you can share.
LabsOfScience
Is designed to check each lane's dual-index pairs against library records and for clashes before the sheet is locked, then show per-lane yield, Q30 and undetermined reads with a re-pool list.
Works with FluidGrids, BigConsole
FluidGrids
Is designed to carry each finished run's lane results from the demultiplexing summary into a BigConsole data sink that feeds the sequencing core's live console.
BigConsole
Is designed to hold alert rules on the lane-quality sink, such as undetermined reads above the core's limit, so the right people hear the morning a run finishes.
LabsOfScience
Records each variant-calling run against a pinned version of the sequencing reads, with its pipeline version, status and log, so a delivered variant file traces to the run that produced it.
AdapterCloud
Is designed to show FASTQ, BAM/CRAM and VCF storage by project, partner and tier, with cost per sample, restore estimates for archived reads and retention-term checks.
Works with LabsOfScience
AdapterCloud
Is designed to attribute cluster hours and cloud spend to each project and partner code, as it does for research awards, and flag a runaway job such as a weekend retry loop to its owner.
SemanticFed
Is designed to line up each access request against the cohort's consent versions, show eligible participant counts, and hold the drafted policy inactive until a committee member approves it.
Works with FluidGrids, LabsOfScience
SemanticFed
Surfaces direct identifiers such as date of birth and hospital number as proposed deny rules that stay inactive until a person approves and activates them.
FluidGrids
Is designed to route a hospital's consent-withdrawal notice by rule: notify the committee, flag past releases that included the participant and request a sample hold.
PlanMagnet
Is designed to show each collaboration milestone with acceptance criteria, payment status and linked evidence, beside committed FTEs and actual effort from approved CrewFoundry hours.
Works with CrewFoundry, LabsOfScience, SemanticFed
CrewFoundry
Holds weekly timesheets with approval status, the approved hours behind each scientist's effort on the collaboration and on internal programs.
PlanMagnet
Is designed to run the government innovation grant beside the collaboration, with aims, deliverables, LabsOfScience experiments and CrewFoundry effort on one timeline.
Healthy Bowl
Is designed to show each site's plots by entry, open permit tasks, seed packet reconciliation and the harvest-window forecast, with CrewFoundry training clearance for each crew member.
Works with CrewFoundry, LabsOfScience
Healthy Bowl
Is designed to let technicians record plot observations and harvest weights with a photo and location stamp where there is no signal, holding them until the tablet reconnects.
CrewFoundry
Is designed to show who is trained on the current version of each stewardship procedure, flag anyone not yet cleared, and assign retraining when a procedure changes.
Pitch kit
Genomics teams run on disconnected tools, and it shows: index clashes found after the run, re-analysis nobody can price, consent tracked in spreadsheets, partner reports rebuilt from memory and trial seed nobody can account for. Burdenoff brings LabsOfScience, FluidGrids, BigConsole, AdapterCloud, SemanticFed, PlanMagnet, CrewFoundry and Healthy Bowl onto one workspace, designed so samples, data, consent, people, partners and field plots connect. A pre-launch solution concept for genomics teams.
Questions
Several. Eight products each handle one part of the work, from samples and sequencing to data costs, consent, partner milestones and field trials. They share one sign-in, one set of permissions, one record of who did what and one bill, and you can start with the two or three that matter most.
Technical detail
Several, each designed to cover one part of the work. LabsOfScience holds runs, analysis and lab inventory; FluidGrids checks finished runs and routes notices; BigConsole shows core quality; AdapterCloud places and prices storage and compute; SemanticFed governs consent-scoped access; PlanMagnet and CrewFoundry handle milestones, people and time; Healthy Bowl runs the trial sites. They share Burdenoff Workspaces for identity, access control, audit and billing, and you can start with the two or three that address your most urgent problem.
No. Your sequencers and analysis tools keep working as they do today. The products are designed to record what those tools produce and connect it, so every result can be traced and every problem reaches the right people.
Technical detail
No. Instrument control and demultiplexing software keep running as they do today, and your pipelines keep their engines. LabsOfScience is designed to record each pipeline run against a pinned version of its input reads with its version and parameters, and FluidGrids is designed to read the outputs your instruments already produce. The aim is to connect what those tools produce, not to replace them.
No. Your data access committee makes every decision. The product is designed to show each request beside what participants agreed to and how many qualify, and nothing opens until a committee member approves it.
Technical detail
No. Your data access committee decides. SemanticFed is designed to show a request's stated use beside the consent codes and the number of eligible participants, and to draft the matching access policy as inactive until a committee member approves it. It does not interpret consent forms or give legal or ethical advice; your committee and counsel set the consent codes and the rules.
No product can promise that. Healthy Bowl is designed to keep the permit tasks you set, where every seed packet ended up and who is trained in one place, so gaps show up early. Your stewardship team stays in charge.
Technical detail
It cannot guarantee that, and it gives no regulatory advice. Healthy Bowl is designed to hold the permit tasks you enter, such as flowering inspections, separate harvest, devitalization and volunteer monitoring, alongside seed packet reconciliation and crew training status from CrewFoundry, so gaps are visible early. Your stewardship team and the regulator remain the authority.
Yes. Partners are designed to get their own sign-in and see only what they are allowed to. Each product keeps its own name and is set up through its settings.
Technical detail
Yes, by design. Burdenoff Workspaces is designed to let you invite partners as members with roles, so a hospital partner, a pharmaceutical alliance team or a cooperating grower sees only the projects, data and tasks they are permitted to. Each product is offered under its own name and configured through its settings.
No. The products are pre-launch, and this page shows how they are designed to work together. Some parts exist in the products today and others are planned, and we are glad to walk through what is available now.
Technical detail
No. These products are pre-launch, and this page describes a solution concept: how the products are designed to work together for biotech and genomics teams. Some capabilities shown are available in the products now and others are on their roadmaps, and the hand-offs beyond the documented FluidGrids-to-BigConsole data sinks and the PlanMagnet and CrewFoundry capacity link are design intent.
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Tell us about your setup. We will walk you through the products involved and scope a pilot around the challenge that hurts most.
This is a solution concept: it shows how Burdenoff products are designed to work together in this industry. The images are illustrations of the concepts, not screenshots of the actual products, and every name and figure in them is sample data.
