Keep up with your team's AI usage

Archival gives managers visibility into how their teams use AI, with direct observability and qualitative analytics at the team level and per user.

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VercelVercel
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A
Team overview
Last 7 days
What did the team accomplish with AI this week?
Active users
12
of 14 members
Top use case
Code review
38% of sessions
Quality signal
Positive
Trending up
Recent activity
S.M.
Drafted client deliverable outline, iterated on structure
via Claude
2h ago
R.K.
Refactored authentication middleware with tests
via Copilot
3h ago
J.L.
Researched competitive positioning for Q2 strategy
via ChatGPT
4h ago

Integrations

OpenAIOpenAI
GeminiGemini
ClaudeClaude
GithubCopilotGithubCopilot
CursorCursor
WindsurfWindsurf
DeepSeekDeepSeek
GrokGrok
PerplexityPerplexity
Not listed? Let us know

The visibility gap

AI changed how your team works. Your visibility didn't.

Your team is producing results with AI, but the process behind those results is invisible. You see the output. You don't see where time went, which tools helped, or where quality is at risk.

Archival surfaces what's happening at the team level and per user, so you can have informed conversations about what's working and what needs to change.

#
#team-ai-updatesvia Archival
Weekly digestToday, 9:00 AM

AI usage increased 18% this week. Code generation remains the top use case. 3 team members started using AI for client communication drafting.

Trend flagYesterday, 2:15 PM

Two users are spending significant time on repeated prompt iterations for data formatting. This may indicate a workflow that could be automated.

HighlightYesterday, 10:30 AM

R.K. used Copilot to complete a 3-day refactoring task in under a day. Test coverage was maintained.

Beyond activity metrics

Understand what your team is doing with AI, not just how much

Most tools count tokens and sessions. Archival contextualizes quantitative data with qualitative insights, so managers can see where AI is creating real value and where workflows need attention.

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Qualitative analytics
Engineering team · March 2026
By use case
By user
By tool
Use case breakdown
Code generation34%
Code review assist22%
Documentation drafting18%
Research and analysis15%
Client communication11%
Quality signals
Code generationHigh quality

Test pass rates stable. AI-assisted code has comparable defect rates to manual code.

Client communicationNeeds review

3 drafts required significant manual revision. Consider shared prompt templates.

Research tasksHigh quality

Faster turnaround on competitive analysis. Sources consistently verified.

Insight

Your team's AI usage is concentrated in high-quality use cases. Client communication is a new and growing category that may benefit from shared guidelines or prompt templates.

AI Adoption Report
Q1 2026 · Executive summary
Export PDF
89%
Team adoption
2.4x
Avg. throughput gain
$42K
Est. quarterly value
Executive summary

AI adoption reached 89% of the engineering team this quarter, up from 64% in Q4. The highest-value use cases remain code generation and code review, which together account for 56% of AI-assisted work. Quality indicators are positive across both categories.

Recommendations
  • 1.Expand AI-assisted code review to the platform team
  • 2.Create shared prompt templates for client-facing drafts
  • 3.Review low-adoption users for training opportunities

Reporting that drives decisions

Turn AI usage data into reports your leadership will read

Archival generates clear, customizable reports that summarize how your team uses AI, what value it creates, and where to invest next. Built for leadership reviews, board updates, and budget conversations.

Stop defending AI spend with anecdotes. Start showing the data.

Security

Built with security in mind from day one

Archival handles sensitive usage data. Our architecture was designed around that reality, not retrofitted for it.

We are early-stage and transparent about where we are. We are happy to walk through our practices in detail.

Encryption

Data encrypted in transit and at rest. Key management follows industry-standard practices.

Tenant isolation

Customer data is logically separated. No cross-tenant access by design.

Access control

Least-privilege access model with role-based permissions. Production access is logged.

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See how your team uses AI

Archival helps managers keep up with team AI usage. Book a demo to see qualitative analytics and direct observability in action.