Recommendations
Timely engagement for every account.
Pravar reviews the whole book and identifies what to do next for each account, with the reasoning attached.
Governed · Agentic · Finance-native
Trusted AI Platform for Financial Enterprises
Pravar AI is the AI intelligence layer that connects your teams and tools, so that you can scale growth, increase margins with compliance and every client still feels like your only client.
~85%
Cost avoidance
~70%
Team capacity freed
20%+
Upsell / cross-sell
+15–20
NPS points from personalization
directional · Modelled — figures vary with a firm's data and adoption.
Backed by the builders of the AI frontier.
In a single year, four of the world's leading AI institutions have recognized Pravar — validating the unique solutions we are building to solve decades-old problems in financial institutions.
for Startups + Antler
Top 30 of 2,000+
Selected for the Immersion Program — hands-on mentorship, technical guidance and access to Google's network.
2026
Inception Program
Innovative Startup
Admitted to NVIDIA's global program for the world's cutting-edge AI startups.
2026
Claude Partner Network
Network Member
Named to Anthropic's programme for firms that help enterprises put Claude to work.
September 2026
OpenAI
Innovator's Hub
Select Partner
Select partner specialized in delivering wealth and asset management solutions.
July 2026
Other Partners
A day in the financial enterprise
The same day,Before and after Pravar.
Across a financial institution, seven roles carry very different days. In each of them the routine work shifts to governed agents, so the people in the role can spend more of their time on judgment and on clients.
Campaigns are personalized to each client, while enriching leads and producing content is largely automated.
- 08:30. Before, without Pravar: Campaigns go out with little personalization, and the same message reaches thousands of households regardless of what they hold or need. After, with Pravar: Campaigns are personalized to each client using the firm’s own data, so the message reflects real portfolios, mandates, and recent life events.
- 12:00. Before, without Pravar: Leads arrive with thin information, and nurturing them relies on follow up that is done by hand whenever someone remembers. After, with Pravar: Pravar enriches each lead with the context the team is missing, and it keeps nurturing them with follow up sent at the right time.
- 16:30. Before, without Pravar: Producing content is slow, because each piece is written, adapted, and cleared largely from scratch. After, with Pravar: Content is drafted automatically from approved material, which leaves the team to review and refine rather than start from a blank page.
Personalized campaigns, enriched leads, and content produced at a fraction of the effort.
Model portfolios are built for real client segments and preferences, and they respond as the macro picture changes.
- 08:30. Before, without Pravar: Clients are served from a small set of standard model portfolios, with little room to reflect the differences between customer segments. After, with Pravar: Pravar builds model portfolios around the firm’s own customer segments, so the construction reflects the real client base rather than a generic template.
- 12:00. Before, without Pravar: When the macro picture shifts, translating it into the effect on individual portfolios is slow and largely manual. After, with Pravar: Macro developments are translated into their effect on each portfolio quickly, and the analyst can see clearly where attention is needed.
- 16:30. Before, without Pravar: Individual client preferences, tax positions, and risk tolerances rarely make it into the portfolio that is actually recommended. After, with Pravar: Portfolios are generated in real time and customized to each client, taking account of stated preferences, tax loss harvesting opportunities, and an assessment of risk.
Each client is served a portfolio matched to their segment, preferences, and tax position.
Reconciliation, order routing, and reporting run with far less manual effort.
- 08:30. Before, without Pravar: Twenty people clear reconciliations line by line, and the exceptions that actually matter are buried in the volume. After, with Pravar: Reconciliation runs with almost no manual effort. A desk of three people handles only the genuine exceptions.
- 12:00. Before, without Pravar: Breaks and order routing are handled by hand and under time pressure. After, with Pravar: Orders route straight through the system, and breaks are surfaced and resolved before they can escalate.
- 16:30. Before, without Pravar: Reporting is assembled manually each cycle, which is slow and leaves room for error. After, with Pravar: Reporting is produced automatically, which shortens each cycle and reduces the errors that come with manual assembly.
About 95 percent of reconciliation completes without manual intervention.Directional estimate.
Specialized research covers more managers, markets, and asset classes than the team could reach by hand.
- 08:30. Before, without Pravar: Due diligence on external managers is slow and involves a great deal of documentation, so the number of managers the team can properly assess stays limited. After, with Pravar: Pravar runs manager due diligence at scale, reading and comparing across documents so the team can assess many more managers with the same effort.
- 12:00. Before, without Pravar: Asset allocation and capital market assumptions are revisited only occasionally, and the long term economic view behind them is difficult to keep current. After, with Pravar: Asset allocation and capital market assumptions are maintained against long term economic assumptions and refreshed as the underlying inputs change.
- 16:30. Before, without Pravar: Macro events tend to be analyzed late, and coverage of alternative investments stays thin because the work takes so much manual effort. After, with Pravar: Macro events are mapped to their portfolio impact quickly, and research into alternative investments is covered within the same process rather than left aside.
85%
Research cost avoidance
5×
Coverage
400%
Analyst productivity
Verified from a live engagement, with no additional headcount.
Oversight runs continuously instead of relying on periodic samples.
- 08:30. Before, without Pravar: Oversight relies on samples, so whatever a portfolio is actually doing between reviews goes unseen. After, with Pravar: Every action an agent takes is observable, explainable, permissioned, and recorded for audit, with evaluations applied at each step.
- 12:00. Before, without Pravar: Every action taken by AI raises a question of how it would be defended, and the rulebook itself is still being rewritten. After, with Pravar: A firm policy layer can only narrow what is permitted and never widen it, and it issues a warning before any limit is breached.
- 16:30. Before, without Pravar: Preparing for an audit means reconstructing the record after the fact. After, with Pravar: The audit record is produced as a natural result of the work rather than assembled afterwards.
The firm is ready for an audit at any point.
Onboarding, support requests, and client reporting are handled quickly, and often during the conversation itself.
- 08:30. Before, without Pravar: Opening an account is a manual process, and it stalls whenever a document is missing or a form comes back not in good order. After, with Pravar: Pravar guides account onboarding, reads the documents, and requests anything that is missing, so accounts open cleanly and quickly.
- 12:00. Before, without Pravar: Answering a support request means searching across several systems while the client waits for the full picture to come together. After, with Pravar: A single unified view of the client lets most support requests be resolved during the conversation itself.
- 16:30. Before, without Pravar: Custom reports are built by hand for each request, which is slow and pulls the team away from clients. After, with Pravar: Custom reports are generated on request, which returns the team’s time to clients.
Relationship manager
Operational work is handled for the advisor, which returns a large part of the day to clients.
- 08:30. Before, without Pravar: The advisor prepares for the nine o’clock review by searching four systems that do not share data, and even then the client’s assets held away from the firm remain an estimate. After, with Pravar: The review opens with a brief that Pravar has already assembled. It covers the full client picture, the assets held away from the firm, recent life events, and a recommended next step.
- 12:00. Before, without Pravar: The most useful insight often appears only once the meeting has ended. After, with Pravar: When the market moves, its effect on each client’s portfolio is already mapped, so the advisor can respond within the meeting itself.
- 16:30. Before, without Pravar: The late afternoon goes to writing up notes and completing the operational tasks left over from meetings, rather than speaking with the next client. After, with Pravar: Notes, tasks, and the operational follow up are handled automatically, which leaves the afternoon for client relationships.
Products
Intelligence
The whole book, in one view.
Accounts, portfolios, held-away assets, house views, and past interactions sit in one view that every role can query and use.
Meetings
Notes captured, actions carried out.
Pravar analyzes each meeting, turns the commitments into assigned action items, and automates the follow-up where it can.
Portfolio
Personalized planning, on demand.
Our engine turns life goals, objectives, and current allocation into recommendations that stay within the firm's views and constraints.
Reporting
Reports in the firm's voice.
Pravar drafts client reports and messages in the firm's voice, and routes each one to the advisor to approve before it sends.
Extensibility
Build your own agents, governed by default.
Compose agents for your own workflows on the same foundation, with the firm's AI policy, permissioning, and audit applied automatically.
Security
Trust is engineered here, not assumed.
Security and data protection are the ground the system is poured on — not a coat of paint at the end. Every action an agent takes is observable, explainable, permissioned, and auditable.
Read the full architecture →AI policy ingestion
Your rules, enforced at inference on every input and output.
PII & NPI redaction
Sensitive data removed before anything reaches a model.
Evals & observability
Every interaction scored, logged, and flagged when it slips.
Single tenancy & self-hosted
Your environment, your keys — cloud, on-prem, or air-gapped.
Live · PII redaction before inference
4 entities masked · policy 7.2 applied · tokens never leave tenancy
Results delivered
“We did not need more analysts. We needed an AI OS that made every analyst exponentially more powerful, while staying compliant. That is what Pravar built.”
CTO · Wealth Advisory firm
We help you cross the chasmfrom Pilots to Production to ROI
Our model
How that result gets built is deliberate.
An engagement that carries your firm from first assessment through to the goals you set, with the burden of proof on us at every step.
Assessment
We start by understanding how your firm works — its processes, its philosophy, and the judgment behind both.
Embedded teams
Our specialists work alongside your teams, tailoring the product to your firm rather than the other way around.
Cross the pilot chasm
Proof at small scale, fine-tuned to the quality your firm will accept, before anything scales to the wider book.
Committed to your success
We stay through change management and adoption, and remain until the goals we set together are met.
Contact us
Let's build something great together.
Please reach out to us for inquiries and partnership.