Technology engagements for land conservation organizations — from strategy through production.
Most conservation organizations make technology decisions reactively — adopting tools under pressure, replacing systems that were never right for the job, and paying ongoing costs for software nobody uses. We help you step back, assess what you actually have, and design a technology plan that matches your operational reality — not someone else's best practices.
A full inventory of every tool, database, and manual process your team relies on — mapped to the work it actually supports.
Conversations with staff, partners, and sometimes communities to understand where friction lives and where systems fail at the edges.
An honest assessment of what exists in the market, what can be configured, and what genuinely needs to be built from scratch.
A prioritized, phased plan with clear rationale — written for leadership, not for engineers.
If procurement is on the horizon, we help you write requirements, evaluate proposals, and avoid the vendor pitches that sound better than they are.
Land trusts and conservation organizations approaching a major technology decision — a new database, a donor management system, a field reporting tool — or those who sense their current stack isn't working but can't articulate why. Also valuable for funders evaluating grantee technology capacity.
6–8 week engagement. Begins with a structured discovery phase (stakeholder interviews, system inventory), followed by analysis and a written strategy document. Delivered as a working session with your leadership team, not just a report in a folder.
AI is genuinely useful for some conservation work and genuinely irrelevant for most of it. The challenge is telling the difference before you've spent six months and a significant budget on a pilot that doesn't deliver. We assess your organization's specific workflows, data quality, and team capacity to identify the narrow set of applications where AI will create real operational value — and the broader set where it won't.
A structured process to surface the specific tasks in your organization where AI could meaningfully reduce burden or improve quality — document review, report drafting, ecological data classification, and more.
AI is only as good as the data it runs on. We assess whether your existing data — in whatever form it lives — is sufficient to support the use cases you're considering.
For organizations working with Indigenous communities or sensitive land data, we identify where AI introduces risks to sovereignty, privacy, or trust — and what guardrails are required.
For high-confidence use cases, we design a time-bounded pilot with clear success criteria so you can evaluate AI performance before committing to a full implementation.
A practical workshop that builds staff fluency with AI tools — focused on your actual workflows, not generic demonstrations.
Organizations that have heard the AI pitch from every direction and want a grounded, skeptical assessment of where it's actually relevant to their work. Also useful for funders considering AI grants or capacity-building investments across a portfolio.
4-week assessment, culminating in an AI Readiness Report: a prioritized list of use cases with honest assessments of feasibility, risk, and expected value. Optionally followed by a pilot design and implementation phase for the highest-confidence applications.
Conservation organizations generate enormous amounts of data — field observations, monitoring records, stewardship reports, ecological assessments, donor interactions — and most of it is effectively inaccessible. It lives in spreadsheets that don't talk to each other, PDFs that can't be searched, and institutional knowledge that leaves when people do. We build the systems that make your data coherent, queryable, and actionable without requiring a data engineering team to maintain.
A structured model for how your data should be organized, stored, and related — designed around your reporting obligations and operational workflows.
Automated connections between data sources — field tools, monitoring systems, donor databases — so data flows to where it's needed without manual re-entry.
Dashboards and reporting tools that answer the questions you actually ask — grant reporting, ecological outcomes, stewardship activity — without requiring a data analyst to pull every report.
Integration with the conservation data standards and systems your funders, partners, and regulators already use — so your data counts in the broader ecosystem.
Every system we build is documented so your team can maintain, extend, and adapt it without depending on us.
Organizations with growing reporting obligations they can't meet efficiently with current tools. Land trusts managing multiple easements with inconsistent records. Conservation programs trying to demonstrate ecological outcomes to funders. Coalitions that need to aggregate data across member organizations.
Scoped based on complexity. A typical initial engagement is 3–6 months, beginning with a data audit and architecture phase before any building begins. We strongly recommend a paid scoping phase before committing to a full build — the design decisions made in the first four weeks determine everything that follows.
Sometimes the tool an organization needs doesn't exist — because the problem is specific enough, or the community it serves has been ignored by mainstream software, or the operational model is sufficiently different from what existing platforms assume. When that's the case, we design and build it. We work from scoping through field-tested launch, with community involvement at every stage that matters.
A rigorous process to define what the platform needs to do, what it explicitly doesn't need to do, and what success looks like before a line of code is written.
Interviews and observation with the actual people who will use the tool — in the contexts where they'll use it. Field workers, not personas.
Interactive prototypes tested with real users before development begins. We find the problems in the design before they're expensive to fix.
A working, deployable product that solves the core problem — built to be extended, not rebuilt. We use modern, maintainable technology that your team or future contractors can work with.
Structured testing in the actual conditions the platform will operate in — including limited connectivity, non-native language users, and the other realities of field-based conservation work.
We don't disappear at deployment. We support the launch period, document everything, and train your team to own what we've built together.
Organizations with a clearly articulated operational problem that no existing tool solves. Coalitions or networks that need shared infrastructure their members will actually adopt. Funders considering catalytic technology investments in a specific conservation domain.
4–12 months depending on scope, always beginning with a paid scoping phase (4–6 weeks). The scoping phase produces a product brief, wireframes, and a development estimate — which you can use to proceed with us or take to another team. We will tell you honestly if the scoping reveals that an existing tool would solve your problem.
Most engagements start with a conversation, not a scope of work. Tell us what you're dealing with and we'll tell you honestly whether and how we can help.