Queryless + Portaljs Upsell Analysis (2026-06-25)

Context

Existing clients have been willing to review brochures and attend sales calls for the new Queryless AI feature, but none have completed a purchase so far. The linked GitHub/GitLab items show that the sales motion has generated interest, but most opportunities are not yet in a qualified buying state.

The core pattern is this: clients are listening, but the process is often stalling before the team has secured a clear budget owner, urgent use case, security/procurement path, and immediate value case.

Current Funnel Read

Bhutan is the strongest near-term opportunity. The demo was well received, a proposal/quote has been sent, but progress is blocked by O&M approval, legal/procurement flow, contract renewal timing, and portal ownership shifting.
SSEN has strong interest, but Queryless would be their first AI feature on the website, so it is moving through security review and roadmap approval.
Malmo liked the idea, but reframed it as an internal-use tool. They are looking for an internal department with a real need, and so far no department has confirmed demand.
Ann Arbor is interested conceptually, but sees limited current value because of low data volume, low website traffic, data normalization problems, and concern about AI overconfidence.
TDC was interested but explicitly said AI is not in their immediate plans.
Zambia/ZDEP needs core platform deployment completed first before an AI upsell makes sense.
Sigma2, Teach for Canada, WRI, and others are not ready because of CKAN upgrades, contract renewals, budget limits, or other active priorities.

Most Likely Reasons Sales Have Not Closed

1. Interest Is Being Mistaken For Purchase Readiness

Many clients are curious and receptive, but curiosity is not the same as an active buying process.

Examples:

Ann Arbor sees Queryless as a future need, possibly 5-10 years out.
TDC wants to be kept updated, but AI is not in their immediate plans.
Malmo is still searching for an internal customer.
Sigma2 and Zambia have prerequisite portal or contract work.

The current process appears to treat positive demo feedback as strong pipeline, even when the client has not confirmed budget, urgency, authority, or timing.

Potential solution: Add a stricter qualification gate before pushing for sale. Score each client on:

Active pain
Data volume and quality
Portal traffic
Internal champion
Budget owner
Security owner
Procurement path
Contract timing
Implementation readiness

Only "close-now" accounts should receive quote/close effort. Other accounts should be placed into nurture, readiness, or prerequisite work.

2. The Sales Process Is Not Consistently Reaching The Real Decision Path

Several blockers sit outside the demo audience:

Bhutan requires O&M, legal, and procurement approval.
SSEN requires security approval because this would be their first AI feature.
Malmo needs an internal department to become the actual customer.
Teach for Canada is waiting on a decision-making director.
Zambia needs investor/client acceptance of the core platform first.

This means a good demo can still stall because the people in the room are not the people who can approve the purchase.

Potential solution: Every sales call should end with a stakeholder map and mutual action plan. Ask directly:

Who approves budget?
Who approves AI/security?
Who signs procurement?
Who owns the operational need?
What must happen before the client can say yes?
What is the next dated decision event?

Then schedule the next meeting with those people, not just send brochures and wait.

3. The Value Proposition Is Not Urgent Enough For Each Client

For several clients, Queryless is perceived as useful but not urgent.

Examples:

Ann Arbor does not believe the current data volume or traffic justifies the investment.
Malmo has not found a department that urgently needs it.
TDC is interested but not ready to prioritize AI.
Sigma2 is focused on CKAN upgrade work.

The pitch seems to prove "this is useful" more than "this solves your current painful problem now."

Potential solution: Replace generic demos with client-specific business cases. For each account, define one urgent workflow, such as:

Reducing staff query burden
Helping internal users find datasets
Improving public dataset discovery
Reducing analyst bottlenecks
Supporting recurring reporting or stakeholder questions
Improving access to complex datasets

If no urgent workflow exists, do not push Queryless yet. Instead, sell an AI-readiness or data-quality package first.

4. Product Trust And Readiness Concerns Are Slowing Adoption

The documented objections are material:

Ann Arbor worries about AI being overconfident with strange data structures.
Malmo reported variable response times.
Malmo saw inconsistent dataset discovery.
Malmo found no way to cancel a search except refreshing the page.
Malmo disliked some UI behavior.
SSEN needs a careful security review because this would be the first AI feature on their site.

These concerns create risk for public-sector or government-adjacent buyers, especially if the AI feature is public-facing.

Potential solution: Create a Queryless "Trust & Readiness Pack" containing:

Security overview
Data handling explanation
Deployment model
Model limitations
Guardrails
Citation/source-link behavior
Answer confidence and "I don't know" behavior
Audit/logging information
Human escalation process
Testing results
Known limitations and roadmap

Product-side, prioritize visible fixes that map directly to client objections:

Improve response speed.
Add cancel/stop search.
Improve consistency in dataset discovery.
Improve handling of messy or unusual data structures.
Offer a quieter UI option.
Make answer provenance and confidence clearer.

5. Some Portals Are Not AI-Ready

Several clients do not yet have the portal maturity needed to justify Queryless.

Examples:

Ann Arbor has limited public data, low traffic, and data normalization issues.
Zambia needs the core platform deployed first.
Sigma2 is focused on CKAN upgrade work.
Teach for Canada is still considering other portal improvements and has limited budget.

In these cases, Queryless is arriving before the foundation is strong enough.

Potential solution: Introduce an "AI Readiness Assessment" or "Data Quality Accelerator" as the step before Queryless.

For Ann Arbor, propose data normalization and portal value/traffic improvements first. For Zambia and Sigma2, attach Queryless as a post-launch or post-upgrade phase rather than an immediate upsell.

6. The Funnel Lacks Strong Closing Mechanics After Demos

The task lists show demos and follow-ups being completed, but proposal, quote, negotiation, contract, and implementation steps often remain incomplete.

Several updates use passive language such as "wait for feedback" or "keep them updated." That is useful for relationship management, but weak for closing.

Potential solution: After each demo, create a concrete close plan:

Decision meeting date
Named business owner
Named budget owner
Named security reviewer
Quote/proposal date
Target approval date
Procurement steps
Implementation start date

No demo should end without a scheduled next decision event.

7. Pricing Or Packaging May Feel Too Large Or Too Final

For uncertain clients, a full Queryless implementation may feel too risky.

Examples:

Malmo may only want internal use.
SSEN may need a controlled first-AI rollout.
Ann Arbor cannot justify a full investment today.
Bhutan may need to fit Queryless into contract renewal and procurement.

Potential solution: Offer lower-friction entry packages:

Paid 60-90 day pilot
Internal-only license
Proof-of-value package
Renewal add-on
AI readiness plus pilot bundle
Limited department-specific rollout

Define success metrics before the pilot, such as:

Number of meaningful queries
Staff time saved
Accuracy threshold
User feedback score
Reduction in support requests
Number of datasets successfully surfaced

Recommended Immediate Actions

Focus Closing Energy On Bhutan And SSEN

These appear to be the most credible near-term opportunities.

Bhutan

Do not just wait for proposal feedback. The next move should be to get clarity on the decision process.

Recommended actions:

Schedule a meeting with the O&M decision owner.
Clarify the portal ownership transition.
Confirm legal and procurement steps.
Identify who approves budget and who signs.
Offer a pilot or renewal-bundled implementation if full purchase approval is slow.
Create a mutual action plan with dates for approval, contract review, procurement, signature, and implementation.

SSEN

Package the sale as a controlled first-AI rollout, not a broad public AI launch.

Recommended actions:

Offer a security workshop.
Provide a Trust & Readiness Pack.
Propose a limited-scope pilot.
Define what the security team needs to approve.
Ask for a roadmap decision meeting with the security owner and product/business owner.
Keep sharing product improvements, especially around reliability, provenance, and controls.

Malmo

Malmo's interest is real, but it is not yet demand.

Recommended actions:

Ask Malmo to nominate one internal department owner.
Ask that department to define one specific workflow Queryless would improve.
Offer an internal-only pilot if a department confirms demand.
If no internal owner emerges within a short window, move Malmo to nurture.

Ann Arbor

Ann Arbor is not a strong immediate Queryless sales opportunity.

Recommended actions:

Pivot away from immediate Queryless sale.
Offer data normalization, data quality, and portal usage improvement work.
Help them address foundational data and traffic issues.
Revisit Queryless once the portal has enough content and usage to justify the investment.

Zambia/ZDEP And Sigma2

These are timing-dependent opportunities.

Recommended actions:

Do not push Queryless before core platform/CKAN work is resolved.
Position Queryless as a phase-two enhancement.
Add it to renewal or post-upgrade planning.
Re-engage once their current project milestones are completed.

Process Changes To Start Completing Sales

Add A Sales Qualification Matrix

Use a simple rating for each account:

Pain: high/medium/low
Urgency: now/soon/later
Buyer identified: yes/no
Security owner identified: yes/no
Procurement path known: yes/no
Data readiness: high/medium/low
Portal maturity: high/medium/low
Budget timing: current cycle/next cycle/unknown
Recommended motion: close, pilot, readiness package, nurture, or defer

Add A Mutual Action Plan Template

After every demo, document:

Client owner
Datopian owner
Business problem
Success criteria
Security/procurement reviewers
Proposal date
Decision date
Contract path
Implementation target
Risks/blockers
Next meeting

Build Objection-Specific Collateral

Create reusable materials for the objections already appearing:

"How Queryless handles overconfidence"
"How Queryless works with messy data"
"Security and governance for public AI features"
"Internal-only deployment option"
"When is a portal ready for Queryless?"
"Pilot success criteria"
"Queryless for low-traffic portals: when to wait and what to fix first"

Create A Pilot Offer

A pilot may convert hesitant clients faster than a full implementation proposal.

Recommended pilot structure:

60-90 days
One portal or one department
Limited scope
Defined success metrics
Security review included
Fixed price
Clear conversion path to annual subscription or full rollout

Feed Product Learnings Back Into Roadmap

The sales blockers contain product signals:

Response speed matters.
Consistency matters.
Cancel search is important.
Messy data handling is a buyer concern.
UI polish can affect trust.
Public-sector buyers need security and governance proof.

Treat these not as one-off objections, but as conversion blockers.

Summary

The lack of completed sales is probably not because clients dislike Queryless. The evidence shows meaningful interest across several accounts. The real issue is that the current motion produces demos and positive conversations before it consistently secures urgency, buyer ownership, security approval, procurement path, and AI/data readiness.

To start closing sales, Datopian should qualify harder, focus near-term effort on Bhutan and SSEN, involve real decision-makers earlier, offer pilots or readiness packages where appropriate, harden the product trust story, and convert every demo into a dated mutual action plan with named client-side owners.

Some clients should not be pushed toward immediate Queryless purchase. Ann Arbor likely needs data quality and portal usage improvements first. Zambia and Sigma2 need core platform or contract work completed first. Malmo needs a real internal owner and use case. These accounts can still become opportunities, but only if the sales motion matches their actual readiness.