Government procurement is supposed to be public, but anyone who has tried to sell into the public sector knows how hard it can be to understand. The information is out there, yet it is scattered across agency websites, meeting minutes, budget files, contract databases, purchasing portals, school board agendas, city council notes, and thousands of documents that rarely speak the same language.
That gap is exactly where Kimia Hamidi is building his next company. As the Co-founder and CEO of NationGraph, Hamidi is working on a problem that sits at the center of public sector sales: how can companies see what government buyers need before the opportunity becomes crowded, slow, or already shaped around another vendor?
NationGraph uses AI to organize public procurement signals and make them easier for sales teams, vendors, and public sector businesses to act on. The company is not simply helping users search for RFPs. It is trying to make government buying behavior more visible by connecting early signals across public records, budgets, purchase orders, contract histories, and agency discussions.
For Hamidi, the bigger story is not just about building another sales intelligence platform. It is about using AI to reduce information gaps in a market where timing, context, and access often decide who gets a fair shot.
Who is Kimia Hamidi
Kimia Hamidi is best known as the founder behind NationGraph, an AI-native platform focused on public sector sales intelligence. His work sits at the intersection of procurement, data, software, and revenue strategy.
Before NationGraph, Hamidi founded Buyer, a pricing intelligence and negotiation-focused company that was later acquired by Ramp. After the acquisition, he worked at Ramp in savings and procurement-related roles, giving him a closer view of how businesses think about pricing, vendor decisions, and cost intelligence.
That earlier chapter matters because NationGraph follows a similar thread. Buyer focused on helping businesses understand whether they were paying fair prices. NationGraph takes that same instinct for transparency and applies it to a much larger and more fragmented market: government procurement.
In both cases, the problem is not that information does not exist. The problem is that the information is hard to find, hard to compare, and hard to turn into confident decisions. Hamidi’s work has repeatedly focused on making complex buying environments easier to understand.
What NationGraph does
NationGraph helps companies discover and act on public sector buying signals. The platform is built for businesses that sell to government entities, especially across state, local, and education markets, often known as SLED.
These markets include city governments, county agencies, state departments, school districts, universities, public hospitals, special districts, and other public institutions. Each one may have its own procurement process, budget cycle, vendor requirements, document formats, and public meeting structure.
For a sales team, this creates a serious research burden. A company might know that its product could help schools, cities, or agencies, but knowing which buyer is ready, which contract is expiring, which budget line was approved, or which department is discussing a new need is much harder.
NationGraph tries to solve this by collecting and organizing procurement-related data from many public sources. That can include:
- RFP releases
- Budget approvals
- Purchase orders
- Meeting minutes
- Contract expirations
- Agency priorities
- Board discussions
- Vendor histories
- Public records
- Buyer contacts
The value is not only in gathering the data. The real value comes from turning messy public information into a clearer picture of buyer intent.
Why government procurement needs more transparency
Government procurement looks open from the outside because many documents are technically public. But public does not always mean accessible. A contract may be listed on one portal. A budget signal may be hidden inside a PDF. A future technology purchase may first appear in a school board discussion months before an official RFP. A vendor replacement opportunity may be buried in an expiring contract notice.
Large companies often have the resources to track these signals manually. They may have public sector sales teams, consultants, channel partners, government relations staff, and years of institutional knowledge. Smaller companies usually do not have that kind of coverage.
This creates an information gap. Vendors that know where to look can move earlier. Vendors that only wait for posted RFPs often arrive late, when the buyer’s needs may already be shaped, relationships may already be formed, and the competition may already understand the account.
That is one reason transparency matters. Better access to procurement intelligence can help more companies understand where genuine demand exists. It can also help agencies hear from vendors that might offer stronger, newer, or more cost-effective solutions but do not have the same insider advantage as established players.
How Kimia Hamidi is using AI to solve the problem
The public sector produces a huge amount of information, but much of it is unstructured. Traditional search tools are not enough when important signals appear across different formats, naming conventions, and document types.
This is where AI becomes useful. NationGraph can help process large volumes of public data and identify patterns that would be difficult for a human team to track manually. Instead of asking a sales rep to read endless meeting notes, budget documents, and procurement portals, AI can help surface the pieces that matter.
For example, a city may discuss replacing outdated software during a public meeting. A school district may approve funding for new security tools. A county may have a vendor contract nearing expiration. A university may create a new role or committee tied to AI, cybersecurity, data systems, or student services. None of those signals are always packaged as a clean sales opportunity. But together, they can point to future demand.
NationGraph’s role is to help users connect these dots earlier. The platform can show what an agency has bought before, who it bought from, what problems are being discussed, what budget activity is taking place, and which opportunities may be forming before a formal solicitation appears.
That shift can change how companies approach government sales. Instead of reacting to posted bids, teams can build account strategies around real public signals.
AI can read what humans do not have time to track
A public sector sales team might care about hundreds or thousands of agencies. Tracking each one manually would require constant monitoring of public meetings, procurement sites, budget documents, contract awards, and administrative updates.
Even a skilled team can miss important signals because the work is too repetitive and too broad. The issue is not intelligence. It is scale.
AI can support that work by scanning large volumes of documents and extracting meaningful information. It can identify topics, entities, vendors, budget language, contract references, and agency priorities. It can also help reduce the time between a signal appearing in the public record and a sales team understanding why it matters.
This matters because timing is a major part of public sector sales. A company that learns about a need six months before an RFP has more time to understand the agency, shape a helpful conversation, gather proof, and prepare a stronger response. A company that discovers the same opportunity after the RFP is published may have less room to stand out.
AI can rank opportunities by relevance
Finding more data is not always helpful by itself. Sales teams do not need thousands of random alerts. They need to know which signals are relevant, timely, and worth action.
That is another area where AI can improve the workflow. NationGraph is designed to help users move beyond basic keyword search by ranking and interpreting buying signals. A raw mention in a meeting document may not be enough. But when that mention connects to a budget line, an expiring contract, a known vendor relationship, or a recent leadership change, it becomes more meaningful.
This kind of intelligence can help teams decide where to spend time. It can also reduce wasted outreach. Instead of chasing every possible agency, vendors can focus on accounts where the public record shows a clearer need.
For companies selling complex products, that context is valuable. A cybersecurity company, an education technology startup, a construction services firm, or a financial software vendor may all need different signals. AI can help match the right opportunity to the right seller.
AI can help vendors act before the RFP
Many public sector sellers treat the RFP as the starting point. In reality, it is often much later in the buying journey. By the time an RFP is published, the agency may have already spent months discussing the problem, studying options, setting budgets, and defining requirements.
That is why pre-RFP intelligence matters. Early signals allow vendors to understand what is happening before the process becomes formal.
For example, a school board might discuss student safety concerns. A city council might approve funding for infrastructure upgrades. A university may appoint a technology leader focused on AI governance. A state agency may mention modernization needs in planning documents. These moments are not always sales opportunities yet, but they can reveal direction.
Kimia Hamidi’s work with NationGraph is built around this idea: public data can tell a story earlier than the official bid if someone knows how to read it.
The role of SLED markets in NationGraph’s growth
The SLED market is a strong fit for this kind of AI-driven platform because it is large, fragmented, and full of public data.
Unlike a single federal procurement system, state and local markets are spread across many institutions. A vendor may need to understand school districts in Texas, county agencies in California, city governments in Florida, public universities in the Midwest, and special districts across dozens of states. Each buyer has its own process and rhythm.
That fragmentation creates pain for sellers, but it also creates an opportunity for better intelligence. If AI can organize those signals into a usable system, companies can approach SLED markets with more confidence.
For NationGraph, the focus on SLED also makes practical sense. These buyers purchase a wide range of products and services, from software and infrastructure to healthcare tools, education solutions, security systems, consulting, transportation, and financial services. The market is broad, but the buying signals are often buried.
NationGraph’s promise is to make those signals easier to see.
Kimia Hamidi’s founder journey from Buyer to NationGraph
Hamidi’s path from Buyer to Ramp to NationGraph shows a consistent interest in markets where better information can create better outcomes.
With Buyer, the focus was price intelligence and negotiation. Companies often struggle to know whether they are paying a fair rate for software and services. Buyer helped bring more clarity to that process.
At Ramp, Hamidi worked closer to savings, procurement workflows, and business spending. That experience likely sharpened his view of how much value can be unlocked when teams have better context before making buying or selling decisions.
NationGraph applies that same thinking to public sector markets. The stakes are different, but the pattern is familiar. When the right data is organized clearly, teams can make smarter decisions. When information is scattered, the advantage often goes to those with the most resources or the longest relationships.
That is what makes Hamidi’s founder story more interesting than a simple startup profile. His work has been shaped by a clear theme: making opaque markets easier to understand.
Why NationGraph’s funding matters
NationGraph’s $18 million Series A funding gives the company more room to build around a problem that has become increasingly important. Public sector sales is a major opportunity for software companies, service providers, infrastructure firms, and emerging technology vendors, but many teams still struggle to enter the market effectively.
The funding also signals investor belief that AI can improve the way businesses understand government procurement. Investors are not only betting on another sales tool. They are betting on a platform that can organize a market that has historically been difficult to navigate.
For Hamidi and the NationGraph team, that backing can support deeper data coverage, stronger AI systems, better customer workflows, and a larger go-to-market operation. In a market where trust and accuracy matter, building the right infrastructure is just as important as building a polished dashboard.
The funding also adds credibility to the idea that public sector intelligence is becoming a serious software category. Private sector sales teams have long used tools for account data, buyer intent, competitive intelligence, and pipeline management. Public sector teams need similar intelligence, but adapted to the way government buying actually works.
How NationGraph could change the way companies sell to government
NationGraph could change public sector sales by making the work less dependent on manual research and personal networks alone.
A small sales team could use the platform to understand which agencies are discussing relevant problems. A startup could find early demand in school districts or cities without hiring a large public sector research team. An established vendor could track contract expirations and budget changes across a wider territory. A revenue leader could prioritize accounts based on real buying signals instead of guesswork.
That does not remove the hard parts of government sales. Vendors still need strong products, clear compliance, patient sales cycles, thoughtful proposals, and real relationships. But better intelligence can help them show up with more context.
When a vendor understands an agency’s priorities, budget reality, existing contracts, and pain points, the conversation becomes more useful. The seller is not just pitching. They are responding to a real need already visible in the public record.
That can benefit buyers too. Government agencies often rely on known vendors because those are the companies they hear from most often. If better data helps more relevant vendors find and understand public needs earlier, agencies may get more options and stronger competition.
More access for smaller vendors
One of the most important parts of NationGraph’s mission is access. Public sector markets are often difficult for smaller vendors because the research burden is high. A small company may have a strong solution but lack the time, staff, or experience to know where to focus.
AI procurement intelligence can lower that barrier. It can help smaller teams understand which agencies are likely to care about their product, what problems are being discussed, and when outreach may be timely.
This does not guarantee success, but it can make the market feel less closed. Instead of relying only on insiders or expensive manual research, smaller vendors can use public data in a more strategic way.
That is where the transparency angle becomes powerful. Transparency is not only about making information visible. It is about making information usable.
Challenges Kimia Hamidi and NationGraph may need to solve
NationGraph is working in a market where data quality is a constant challenge. Government records can be inconsistent, incomplete, outdated, duplicated, or difficult to classify. One agency may publish clean procurement data. Another may upload scanned PDFs. Another may bury key details inside meeting packets.
For AI to be useful in this environment, accuracy matters. Sales teams need to trust the signals they receive. If the platform surfaces too many weak alerts, users may ignore it. If it misses important context, teams may make poor decisions.
There is also the challenge of interpretation. A budget approval does not always mean a purchase will happen. A meeting discussion may point to interest, but not urgency. A contract expiration may create an opportunity, but the incumbent may still be favored. NationGraph must help users understand signals without oversimplifying them.
Trust will also matter as AI becomes more involved in public sector workflows. Vendors need explainable intelligence, not black-box guesses. Government buyers may also care about how public data is collected, processed, and used.
These are not small challenges, but they are part of what makes the opportunity meaningful. If NationGraph can help teams make sense of messy public records with enough accuracy and context, it can become a valuable layer in the government sales process.
Why Kimia Hamidi’s work stands out
Kimia Hamidi’s work stands out because NationGraph is focused on a market where better information can change who gets to compete. Government procurement is large, important, and technically public, yet it remains difficult for many businesses to understand.
By using AI to organize public sector buying signals, Hamidi is building toward a more transparent system for companies that serve government buyers. The achievement is not just raising funding or launching a platform. It is identifying a real information gap and building technology around it.
NationGraph sits at the point where public records, sales intelligence, procurement strategy, and AI meet. That makes Hamidi’s current work especially relevant for businesses trying to enter or grow in state, local, and education markets.
In a field where timing and context can decide everything, NationGraph is trying to give more companies a clearer view of what is happening before the official opportunity appears.
