RESEARCH QUESTION / LITERATURE SOURCE / EVIDENCE ASSESSMENT

AI agent for scientific literature research teams

Keep the claim attached to the study that supports it.

Search relevant literature, reconcile study evidence and maintain research updates—carried through by an autonomous AI agent that adapts to your work.

A specialised AI agent you can ask for more. Chat here on the site.
$249.00/month, including $50.00 in monthly credits. Monthly subscription. Before tax.

Specialised AI agentYour own report presetNo connection needed to begin
Research question workbenchSPECIALIST / 1138
Maintain research updates. With the source records attached.ILLUSTRATIVE STUDY
YOUR SPECIALISED AI AGENT

One place for search relevant literature, reconcile study evidence, maintain research updates.

MADE FOR YOUR WORKDAY

Start with work already on your desk

Your first useful assignment.

Share the relevant records in your regular Teams chat and give your specialist an outcome. No model or tool choices to make first.

Get my AI agent →
YOU COULD ASK
“Build the evidence review for our new research question, resolve contradictory findings and deliver a source-linked synthesis with an update plan.”
  • Search relevant literature
  • Reconcile study evidence
  • Maintain research updates

A useful first result
An editable research question and evidence assessment register with traceable references, resolved discrepancies and specific next actions.

Example assignment, not a promised delivery time. Your agent works from the records and access you provide. Add connections when you want it to act in other systems.

A conversation at your desk

Build the evidence review for our new research question, resolve contradictory findings and deliver a source-linked synthesis with an update plan.

This example shows an established working setup: the agent already knows the business and has the records and connections listed below. Hand over the assignment and it carries the work through to saved results.

Illustrative project · configured agent at work

A configured agent with your research question, literature source, evidence assessment records, current commitments and the connected accounts used to reconcile study evidence.

  • Search relevant literature
  • Reconcile study evidence
  • Maintain research updates

A working specialist can handle the project, with a configured team sharing the work where available. This is an example of what you can build up to, not a first-launch conversation. Timing and usage depend on the assignment.

  1. You · Scientific literature research teams

    Build the evidence review for our new research question, resolve contradictory findings and deliver a source-linked synthesis with an update plan.

  2. Your AI agent · AI Agent Store

    Two widely cited findings use different populations and one paper has a correction. I am reconciling those before summarising the evidence.

    Work in progress
  3. You · Scientific literature research teams

    Keep exclusions documented and preserve contradictory results in the review.

  4. Your AI agent · AI Agent Store

    The synthesis includes traceable claims, documented inclusion decisions and clearly stated evidence gaps and disagreements. Your working files and dashboard reflect the recorded outcomes.

    Later · delivery and saved results

The details your specialist follows

Working records for scientific literature research teams

Follow each research question through the working record. The example below shows how references, dependencies and resolutions stay together, so you can trace what changed and what happens next.

Keep an eye on: changes in literature source, missing evidence assessment evidence and unresolved research question dependencies.

Illustrative working document · your records start empty

Research questionDependency to followEvidence of completion
OPPORTUNITY112-104Search relevant literatureCitation discrepancies resolved
OPPORTUNITY112-118Reconcile study evidenceStudy assessments completed
OPPORTUNITY112-126Maintain research updatesResearch review deadlines met
Active research question records3
Candidate studies across the planned work175 candidate studies
Outcomes with supporting evidence2

Illustrative project figures. Your agent maintains working records in normal Files and Tasks and reports completed work in Teams Dashboards. Ask it to adapt those records and reports as your workflow changes.

RESEARCH QUESTION / LITERATURE SOURCE / EVIDENCE ASSESSMENT

A working brief for your AI agent.

Preserve search strategy, inclusion criteria, publication versions and study limitations. Check original sources for substantive claims and distinguish preliminary findings, retractions and established evidence. Your specialist maintains these working records in regular Teams as the assignment develops.

AI

Your AI agentPrepared for scientific literature research teams

Research question and evidence assessment registerEXAMPLE, NOT LIVE ACTIVITY

An example record for research question, literature source, evidence assessment, candidate studies.

01Research question02Literature source03Evidence assessment

The useful next step

Search relevant literature

Search relevant literature using the current research question and its supporting records.

Built around the details that matter

Search relevant literature. With the right questions already in mind.

Systematic literature investigation, distinct from manuscript writing and journal publishing.

01

Search relevant literature

Search relevant literature using the current research question and its supporting records.

02

Reconcile study evidence

Reconcile study evidence while keeping literature source changes traceable.

03

Maintain research updates

Maintain research updates with checked evidence assessment evidence and editable working files.

A small tool for a real job

Candidate studies across the planned work. Before the back-and-forth.

Watch for changes in literature source, missing evidence assessment evidence and unresolved research question dependencies. Investigate the cause, carry useful follow-through to completion and improve the saved method when it helps.

Try the numbers, then bring the confirmed brief to your specialist. Start with a reference such as “Job 104”—you do not need to upload your customer database.

  • Research question
  • Literature source
  • Evidence assessment
  • Candidate studies

Try your own numbers

Candidate studies across the planned work

175candidate studies across the planned work

Planning arithmetic from your inputs. Your specialist can turn the confirmed details into a working brief. This is not a quote or capacity commitment.

From enquiry to a useful next step

Research question and evidence assessment register. Your way of working.

01

Brief and source records received

Add a job reference and the details you already know.

02

Search relevant literature

Research question and Literature source, ready to check.

03

Reconcile study evidence

Give your specialist the outcome and let it carry the work forward.

04

Outcome evidence verified

Keep working records in Files and Tasks.

05

Maintain research updates

Keep the job and its next steps together.

Ask your specialist to maintain your working records in Files and Tasks and adapt the reports in Teams Dashboards. These are the regular platform tools, prepared for your business. Connections to other systems are optional.

Prepared for your business

The numbers behind your ai agent for scientific literature research teams.

Six useful measures, ready in your regular Teams dashboard. Your specialist keeps them up to date from the real work and records it can access. Ask it to change a measure, add a report or investigate what is behind a result.

01

Recorded cases · outcomes

Literature reviews delivered

What this measures

Count one distinct observed outcome for “Literature reviews delivered”, linked to its research question and stable completion-event ID. Use the real completion timestamp and supporting evidence assessment reference. Pending, merely promised, repeated and illustrative outcomes do not count. Revisions or corrections replace the original event rather than creating duplicate completions.

02

Recorded cases · outcomes

Citation discrepancies resolved

What this measures

Count one distinct observed outcome for “Citation discrepancies resolved”, linked to its research question and stable completion-event ID. Use the real completion timestamp and supporting evidence assessment reference. Pending, merely promised, repeated and illustrative outcomes do not count. Revisions or corrections replace the original event rather than creating duplicate completions.

03

Recorded cases · outcomes

Study assessments completed

What this measures

Count one distinct observed outcome for “Study assessments completed”, linked to its research question and stable completion-event ID. Use the real completion timestamp and supporting evidence assessment reference. Pending, merely promised, repeated and illustrative outcomes do not count. Revisions or corrections replace the original event rather than creating duplicate completions.

04

Average · hours

Search scope agreed to evidence synthesis

What this measures

Measure “Search scope agreed to evidence synthesis” in elapsed hours using the actual start and end timestamps for the same research question. Store one duration per completed observation with source references and timezone. Exclude pending cases, missing timestamps, reversed intervals and illustrative values. Never substitute a current status or sum recurring snapshots.

05

Observed rate · %

Research review deadlines met

What this measures

Completed commitments assessed for “Research review deadlines met”, linked to stable research question references. Numerator: on_time; denominator: on_time plus late from the same assessed population. Classify each observation once and preserve failures. Exclude pending or unknown cases, unassessed records and illustrative values. Compare actual completion with the original agreed deadline and timezone; never move the deadline to improve the result. Corrections replace the original event instead of counting twice.

06

Observed rate · %

Claims supported by assessed sources

What this measures

Completed assessments for “Claims supported by assessed sources”, linked to stable research question references. Numerator: passed; denominator: passed plus failed from the same assessed population. Classify each observation once and preserve failures. Exclude pending or unknown cases, unassessed records and illustrative values. Apply the documented requirement or acceptance checklist and retain the actual supporting evidence; do not infer a pass from an administrative status. Corrections replace the original event instead of counting twice.

Your reports start empty. Figures reflect observed work in the selected period; missing records are not treated as measured zeroes. Current jobs, schedules and stock stay in your working files and tasks. You and your agent can adapt the dashboard as your business changes.

Keep the tools that already work

Specialised in your trade. Open to your next idea.

Your AI agent starts with the details of your business already in mind. The three workflows are starting points. Ask it for help with another task in the same conversation.

An AI agent prepared for your business

The starting instructions, intake questions and working rules already match scientific literature research teams. Add your service list and one example of your tone when you are ready.

Give your agent the whole job

Give your agent an outcome, the access it needs and your budget. It handles routine decisions and follows through in your connected tools, asking when a missing business decision needs you. Set or change your own boundaries whenever you want.

Ask beyond the starting workflows

Your agent can take on a new assignment, build a new workflow, improve its saved methods and adapt its dashboard as your needs evolve. The starting examples do not limit its capabilities. Give your agent another task in plain language. What it can carry out depends on the tools you connect and the access you choose.

Recommended starting plan

Your AI agent for scientific literature research teams.

Begin with one specialist and a report preset for your business. After setup, your regular Agent Teams conversation opens. No tool selection before your first conversation.

$249.00/month

Capacity for 1 running agent · hosting throughout the month

Start my AI agent →

A clear starting total

Your Agent plan is $199/month with hosting included. This recommended offer adds $50 in monthly Platform Credit funding, for $249/month.

$249.00 before tax today and monthly, including $50.00 in monthly Platform Credit funding.

Credits offer an easy start and unused credits roll over. You can switch to your own subscriptions or API keys anytime, with no Platform Credits needed for that AI work. Hosting is included within your agent’s resource allocation. Optional voice and other services use credits.

Hosting availability is checked before payment. Create your account, confirm your monthly subscription, then start chatting when your specialist is ready. Your instructions and dashboard are prepared automatically after payment.

Other plans and connection options →

Prefer your own AI accounts? Choose a plan without the extra $50 monthly credit funding using the options above. Changing AI access alone does not remove that funding. Automatic top-ups start off; buy credits or set top-ups and spending limits when needed. Keep the full Teams controls for models, connections and supported settings.

Before you begin

An AI agent for scientific literature research teams.

How does the agent keep research question work accurate?

Preserve search strategy, inclusion criteria, publication versions and study limitations. Check original sources for substantive claims and distinguish preliminary findings, retractions and established evidence. It keeps source references with the working files, checks the result and follows up on discrepancies. Ask it to adjust the method or report whenever your needs change.

Is this only for the three tasks shown?

No. This is an AI agent specialised for scientific literature research teams, with three prepared workflows to get you started. You can ask for writing, research, planning, analysis or another task in the same chat. It can make routine decisions and carry the work through using available tools. You set its boundaries; it asks when a real business decision or missing access needs you.

What happens after I subscribe?

After payment, we prepare your AI agent for scientific literature research teams, its workflows and your research question and evidence assessment register dashboard. Your regular Agent Teams chat opens when setup is ready. Files, Tasks, settings and billing work the same as for other customers. Reports start empty and count actual reported work; the examples above are illustrative.

Do I need to connect email or messaging?

No. Prepare your first brief and draft here. Connect external channels later when you want the specialist to work there.

Does this replace my existing business software?

Use it alongside your current tools for preparing work and organising jobs. Live stock, availability, sending and payment records require a verified connection or your own confirmation.