What they do
tracing, evals and gateway to watch and fix AI agents
How close to us
5, very close
checks only; watches agents and surfaces failures, W2 head on, sold to AI startups
Wedges
- W2 Seeing whether your AI agents actually produce direct
- W1 Trusted 24/7 coding for small startup teams adjacent
- W8 The other 90% of an AI skill adjacent
Who buys
- Firm size
- sme
- Buyer type
- developer
- Role
- AI engineer, head of AI or CTO at an AI startup
- UK
- not known
Their own description (from YC)
Respan gives teams a unified control plane to trace and evaluate agent behavior without guesswork, automatically surface issues, and fix what breaks faster. Respan connects production observability, automated and human-in-the-loop evaluations, and an adaptive AI gateway to close the loop between detection, decision, and action - so agents improve continuously in production.
Respan is trusted by 100+ AI startups and enterprise teams. Today, the platform process 1B+ logs and 2T+ tokens every month, supporting more than 6.5M end users.
Full teardown
Respan (YC Winter 2024): teardown vs XMarts
In one line: Respan sells AI engineers a gateway, tracing, evals and alerts to watch and fix the AI agents they ship, with a free tier and a $199 a month team plan [site] [yc]. Threat: 3, because it is the clearest W2 rival: same kind of buyer, same "is my agent working?" problem, funded, live, with named customers, and it already traces Claude Code, Codex CLI and Cursor runs [press] [site] [docs].
1. Fact file
| Item | Finding | Source |
|---|---|---|
| What they say | Home page: "The AI router with built-in observability & automated evals." YC line: "Self-driving observability, evals, and gateway for AI agents." | [site] [yc] |
| Founded, team, funding | Founded 2023. YC page shows 23 people; their careers page says about 10 (the two disagree). $5M seed announced 18 Mar 2026, led by Gradient (YC, Hat-Trick Capital, Xiaoxiao Fund, Antigravity Capital, Alpen Capital also in). One data site lists $5.5M over 2 rounds, counting a 2024 convertible note. | [yc] [site] [press] |
| Founders | Andy Li (CEO; ex-Apple product design, UIUC dropout). Raymond (co-founder, UIUC, named in the old launch post). A data site also names Hendrix Liu as co-founder, and he writes on their blog. What YC likely saw: a young technical team shipping fast on a hot infrastructure problem (inference). | [yc] [press] [blog] |
| Customers | Case studies: Retell AI, Mem0, Octolane, Finta, Apten. Testimonials: AlphaSense, Lovable, Gumloop and about 40 more, mostly AI-native startups. They claim "100+" AI startups and enterprise teams, 1B+ logs and 2T+ tokens a month, 6.5M+ end users. A press release adds a claim of 8x revenue growth in 2025, with no base number. | [site] [yc] [press] |
| Price | Public. Free: 100k logs. Team: $199 a month, 5 seats, extra seats $15, extra logs $8 per 100k. Enterprise: custom, self-hosting, SAML. HIPAA add-on $249 a month. Job ads: first GTM hire paid $100k to $150k. | [site] [jobs] |
| Path | Keywords AI (YC W24 launch: "unified DevOps platform" for AI apps, gateway, prompt management, logs, evals, fine-tuning) → renamed Respan, post dated 20 Feb 2026 → $5M seed and "proactive" launch 18 Mar 2026 → Launch Week 20 to 24 Apr 2026 (Monitors, Evals 2.0, Agent/CLI/MCP) → Router and Guardrails 28 Sep 2026 → Span-02 decision model 15 Oct 2026. | [yc] [blog] [press] |
2. Their proposition, reverse engineered
| Part | What they do |
|---|---|
| Who buys | Engineers and founders at AI startups (voice, CRM, memory, accounting agents). Named contacts are mostly CTOs and founders [site]. Enterprise plan exists but case studies are all small firms (inference from [site]). |
| The pain | AI answers that "look valid" but are wrong, incomplete or off-brand, and that raise no error [press]. Debugging agents is slow. In-house tracing drifts and has no owner [blog]. |
| The promise | One control plane to trace, score, route and fix agents so quality improves in production [site] [blog]. |
| How it works | Send model calls through their gateway or add tracing with one CLI command. Every call, tool run and agent turn becomes a span. Automated judges score live logs. Alerts go to Slack, email or webhooks [site] [docs]. An "evaluation agent" finds root causes and suggests new evals and prompt changes [press]. |
| The output | Dashboards, alerts, scored logs, grouped error incidents, prompt versions. For some errors a "Copy fix prompt" button that hands a coding agent the failing spans via MCP [blog]. |
| Proof style | Volume and speed: logs and tokens processed, "90%" less debugging time (Octolane), 1M+ hourly calls (Retell), 4.4M agent requests (Octolane). All claimed by them [site] [blog]. |
| Who sells it | Self-serve free tier plus card plan, enterprise by contact. Hiring a "Founding Technical GTM" and a marketing lead. Heavy search content: "best alternative to X" posts [site] [jobs] [blog]. |
| Price model | Seats plus usage (logs and scores) [site]. |
| The story | Belief: "Agent quality requires a control plane." Foe: tools that "stop too early" at measurement, and DIY tracing [blog]. |
3. Positioning
- Category they claim: "first proactive AI observability platform" and "control plane" for agent quality [blog].
- Category a YC partner would put them in: LLM observability and gateway (Langfuse, Braintrust, LangSmith, Portkey space) (inference).
- What they want to be known for: observability that does not stop at a dashboard but turns what it sees into a fix.
- Where they sit on the map: layers L1/L2/L3 = 0/1/1, buyer = sme, developer.
4. Three layers vs ours
| Layer | Them (score + evidence) | Us (Marton's logs show) |
|---|---|---|
| L1 Company brain | 0. Stores traces, prompts and test sets for the customer's app. No memory of the customer's company [site]. | A vault of about 1,400 pages, 112 call transcripts and about 8,700 customer quotes, searchable by meaning. |
| L2 Agent orchestration | 1. "Respan Agent" is one assistant inside the product that reads and writes platform items (monitors, prompts) [blog]. It does not run a team of agents on the customer's work. The gateway routes model calls, not agents (inference). | About 5,600 jobs run by agents from three makers, each checked by a different AI, then automatic tests. |
| L3 Execution and learning | 1. Checks only. Scores live output, groups errors, suggests fixes. The fix is left to the customer or their coding agent [blog]. Press says it turns results into "prompt updates" [press]; no public proof it applies them (UNVERIFIED). | Every failure gets a record and an automatic check (about 160 records). Offer feedback lines fell from 44 to 18 as rules were added. Only about 15% of jobs reached the main code. |
5. Same and different
| Topic | Same or different | Them | Us |
|---|---|---|---|
| Core belief | Same | Agents fail quietly; you need to see and score them in production [press]. | Same (brief W2: what is stuck, what silently failed, what it costs). |
| What is watched | Different | Agents inside the customer's product (voice bots, CRMs) [site]; also coding-agent runs via tracing hooks [docs]. | Marton's logs show it watches the agents that do the team's own work: a job queue through to merge. |
| Unit of proof | Different | A trace, a score, a log count [site]. | Marton's logs show a job that lands: 5,641 jobs, 864 merged. |
| Buyer | Same | AI engineers at small tech firms [site]. | Small startup teams running coding agents (brief W1/W2). No customer yet. |
| Who fixes | Different | Customer edits prompt or code, optionally via a copied fix prompt [blog]. | Marton's logs show failures become automatic checks that block the repeat (inside our own system only). |
| Delivery | Different | Software, self-serve first [site]. | A running system plus the two founders. |
| Price | Different | $0 or $199 a month plus usage [site]. | Not set yet. |
| Maturity | Different | 100+ customers (they claim), $5M seed, shipping weekly [press] [blog]. | Zero customers; first-hand failure history only (inventory). |
6. Wedge overlap
| Wedge | Fit | Why |
|---|---|---|
| W2 Seeing whether your AI agents actually produce | direct | Same promise to the same kind of buyer. They trace Claude Code, Codex CLI, Cursor and Gemini CLI runs [docs], monitor cost and errors, and group failures into incidents [blog]. |
| W1 Trusted 24/7 coding for small teams | adjacent | They do not run coding agents. They watch them and can feed failures back to one through MCP [blog] [docs]. |
| W8 The other 90% of an AI skill | adjacent | Evals, regression checks and prompt versions touch upkeep of prompts [blog]. No public claim about skills, retiring dead ones or staleness (UNVERIFIED that none exists). |
7. Whitespace (where they stop)
- Layer gap: they check; they do not do the customer's work, and they hold no memory of the customer's company [site]. To own it we need a customer's agents to do real work, with the check and the memory in one loop, for 4+ weeks.
- Number gap: their numbers count volume, speed and uptime, not finished work (logs, calls, "90% less debugging time") [site] [blog]. To own it we need one number a buyer signs: work accepted, landed or paid, per week, with cost per unit.
- Buyer gap: not found as a gap. They sell to the same small tech teams, at a low price [site]. Do not claim it.
- Price gap: not found. A free tier and $199 a month is cheaper than anything we would charge [site]. Do not claim it.
- Speed gap: not found. One CLI command and "traces within minutes" [press] [docs]. Do not claim it.
8. For the YC application
- Proven today: Marton's logs show a fleet that has run 5,641 agent jobs, with 864 merged. About 160 incident records each name a failure class and an automatic check. One record shows a single launch that authorised 156,000 agent turns and used 39% of a weekly budget in 14 hours. Respan's public pages count calls and logs, and no page we found counts work landed [site] [blog].
- Draft answer to "how are you different from Respan?": DRAFT. "Respan shows you what your agents did, call by call. We track whether the work landed, and we turn each failure into a check that stops it coming back. We learned this by running our own agent fleet for five months." Founders say it their own way.
- Future claim (needs proof): "We show a small team how much agent work was accepted each week and what it cost per piece." Needs one customer's agent fleet watched for 4+ weeks, with a before/after number, and a build that does not depend on our Macs (inventory weakness).
- What we understand that they don't: the failure that matters is not a bad answer but a job that quietly never lands, and the fix is a rule, not a dashboard.
provenon our own fleet;needs proofon a customer. - Copyability (M3): medium. The tracing and alerting parts are easy for them: they already ship coding-agent tracing, error incidents, monitors and an MCP with 40+ tools [docs] [blog], and their buyer uses these agents (inference). The part that is harder is tying traces to landed work and the named failure classes, which needs the merge side and months of operating history (inference). Not
hard, so M3 can not score above 3 against Respan. - Why now (M4): None found in this teardown. Respan's own dated moves (rebrand 20 Feb 2026, "proactive" launch 18 Mar 2026) show the market is moving to closed-loop observability [blog] [press], but that helps Respan as much as us.
- Do not claim: "no one watches coding agents" (Respan traces four of them [docs]). "Self-driving observability is hype" (we found no autonomous fix claim from them, only suggestions; we have not tested the product). "Cheaper" or "faster to set up" (their price and setup are very low). Any customer count or revenue of our own.
9. Ideas worth taking
- A "Copy fix prompt" button: hand a failure plus its evidence to a coding agent in one click [blog].
- Group many failures into one incident and label whose fault it is (provider, your requests, platform) [blog]. Easy to act on.
- Rank-style content: "best alternative to X" comparison pages that catch buyers who are already searching [blog].
10. Unknowns
- True team size (YC says 23, careers page says about 10). Look at the YC page and their careers page again in a week.
- Revenue and growth. They claim 8x in 2025 with no base [press]. Ask investors or look for a Gradient post.
- Whether their coding-agent tracing shows stuck, retried or never-landed jobs, or only calls. Read
respan.ai/docs/integrations/claude-code; ideally run the free tier on one of our own jobs. - Whether the "evaluation agent" applies prompt changes by itself or only suggests. Docs and launch posts do not say.
- Sales motion. The Founding Technical GTM ad body sits behind a YC login.
- UK or European customers. None seen.
Sources
- respan.ai home [site]
- Respan pricing [site]
- Respan customers [site]
- Respan careers [site]
- Respan docs [docs]
- Respan docs index (llms.txt), coding-agent integrations [docs]
- YC company page [yc]
- YC jobs page [jobs]
- Announcing our new brand: Respan, 20 Feb 2026 [blog]
- Respan Agent, CLI and MCP (Launch Week day 3), 22 Apr 2026 [blog]
- Error tracking in Respan, 13 Oct 2026 [blog]
- Introducing Span-02, 15 Oct 2026 [blog]
- How Octolane scaled to 4.4M agent requests, 30 Sep 2026 [blog]
- Respan blog index [blog]
- SiliconANGLE: Respan raises $5M, 18 Mar 2026 [press]
- VCA Online press release, 18 Mar 2026 [press]
- CB Insights, Keywords AI financials (via search result, not opened) [press]
Technical detail
- Slug
- respan
- Lens hash
- 179096c479
- Pass
- deep
- Stale
- no